diff --git a/agent/pet/generate/__init__.py b/agent/pet/generate/__init__.py
new file mode 100644
index 00000000000..b75a03cd985
--- /dev/null
+++ b/agent/pet/generate/__init__.py
@@ -0,0 +1,29 @@
+"""Pet generation — base-draft → hatch pipeline.
+
+Public surface used by the gateway RPCs, the CLI ``hermes pets generate``
+command, and tests:
+
+- :func:`generate_base_drafts` / :func:`hatch_pet` — the two-step flow.
+- :class:`HatchResult`, :class:`GenerationError`.
+- :mod:`atlas` — deterministic frame extraction + atlas composition/validation.
+
+Image generation is delegated to the active reference-capable
+:class:`~agent.image_gen_provider.ImageGenProvider` (OpenAI gpt-image-2 or Krea);
+atlas assembly is fully deterministic so it's testable without any API calls.
+"""
+
+from __future__ import annotations
+
+from agent.pet.generate.imagegen import GenerationError
+from agent.pet.generate.orchestrate import (
+    HatchResult,
+    generate_base_drafts,
+    hatch_pet,
+)
+
+__all__ = [
+    "GenerationError",
+    "HatchResult",
+    "generate_base_drafts",
+    "hatch_pet",
+]
diff --git a/agent/pet/generate/atlas.py b/agent/pet/generate/atlas.py
new file mode 100644
index 00000000000..8559ddb530d
--- /dev/null
+++ b/agent/pet/generate/atlas.py
@@ -0,0 +1,724 @@
+"""Deterministic spritesheet assembly — generated row strips → Hermes atlas.
+
+Image-generation models are good at *drawing* a row of poses but bad at exact
+grid geometry, so the model never owns the atlas layout: it produces one loose
+horizontal strip per state, and these deterministic ops slice that strip into
+clean, centered, transparent ``192x208`` cells and pack them into the sheet our
+renderer reads.
+
+The atlas follows the **petdex/Codex standard**: 8 columns x 9 rows of
+``192x208`` cells (``1536x1872``), with the row order + per-row frame counts
+from OpenAI's ``hatch-pet`` skill. Our renderer (:mod:`agent.pet.render`) keys
+frames as ``rows = states, cols = frames`` via
+:data:`agent.pet.constants.CODEX_STATE_ROWS`, and a pet built here is a valid
+``petdex submit`` spritesheet. Rows shorter than 8 columns leave the trailing
+cells fully transparent.
+
+Note ``running`` is the *working* state (in-place processing), NOT locomotion —
+``running-right`` / ``running-left`` are the actual directional walk cycles.
+
+The frame-segmentation, fit-to-cell, and transparency-residue logic is adapted
+from OpenAI's ``hatch-pet`` skill (openai/skills, Apache-2.0).
+"""
+
+from __future__ import annotations
+
+import io
+import logging
+import math
+from pathlib import Path
+
+from agent.pet.constants import FRAME_H, FRAME_W
+
+logger = logging.getLogger(__name__)
+
+CELL_WIDTH = FRAME_W
+CELL_HEIGHT = FRAME_H
+
+# (state, row index, frame count). Order/row indices MUST match
+# ``constants.CODEX_STATE_ROWS`` so the renderer crops the right row for each
+# driven state, and the per-row frame counts mirror the petdex/Codex
+# ``hatch-pet`` ``animation-rows`` spec. The renderer trims trailing blank
+# columns, so rows shorter than ``COLUMNS`` (8) just leave the tail transparent.
+ROW_SPECS: list[tuple[str, int, int]] = [
+    ("idle", 0, 6),
+    ("running-right", 1, 8),
+    ("running-left", 2, 8),
+    ("waving", 3, 4),
+    ("jumping", 4, 5),
+    ("failed", 5, 8),
+    ("waiting", 6, 6),
+    ("running", 7, 6),
+    ("review", 8, 6),
+]
+
+ROWS = len(ROW_SPECS)
+COLUMNS = max(count for _, _, count in ROW_SPECS)
+ATLAS_WIDTH = COLUMNS * CELL_WIDTH
+ATLAS_HEIGHT = ROWS * CELL_HEIGHT
+
+FRAME_COUNTS: dict[str, int] = {state: count for state, _, count in ROW_SPECS}
+
+# Alpha at/below which a pixel is "background" for component detection.
+_ALPHA_FLOOR = 16
+# Cell padding kept around a fitted sprite so poses never touch the edge.
+_CELL_PAD = 10
+# Margin for the normalized pass — small, to fill the cell like real petdex pets
+# (they sit ~5px from the edges); the width clamp, not the pad, prevents clipping.
+_NORMALIZE_PAD = 14
+# Side-lobe cutoff for fitted frames. Adjacent-pose bleed usually appears as a
+# small separated horizontal lobe beside the real subject; keep sizeable lobes so
+# we don't punish a legitimate wide pose.
+_SIDE_LOBE_RATIO = 0.18
+
+
+# ───────────────────────── background removal ─────────────────────────
+
+
+def _color_distance(r: int, g: int, b: int, key: tuple[int, int, int]) -> float:
+    return math.sqrt((r - key[0]) ** 2 + (g - key[1]) ** 2 + (b - key[2]) ** 2)
+
+
+def _has_transparency(image) -> bool:
+    """True if the strip already carries a real alpha background."""
+    extrema = image.getchannel("A").getextrema()
+    # Min alpha 0 somewhere and a meaningful share of fully-transparent pixels.
+    if extrema[0] > _ALPHA_FLOOR:
+        return False
+    hist = image.getchannel("A").histogram()
+    transparent = sum(hist[: _ALPHA_FLOOR + 1])
+    total = image.width * image.height
+    return transparent > total * 0.05
+
+
+def _dominant_corner_color(image) -> tuple[int, int, int]:
+    """Sample the four corners and return the most common opaque color."""
+    from collections import Counter
+
+    w, h = image.width, image.height
+    px = image.load()
+    counter: Counter = Counter()
+    for x, y in ((0, 0), (w - 1, 0), (0, h - 1), (w - 1, h - 1)):
+        r, g, b, a = px[x, y]
+        if a > _ALPHA_FLOOR:
+            counter[(r, g, b)] += 1
+    if not counter:
+        return (0, 255, 0)
+    return counter.most_common(1)[0][0]
+
+
+def _near_key_mask(image, key: tuple[int, int, int], tol: int = 48):
+    """An ``L`` mask, 255 where a pixel is within *tol* per-channel of *key*.
+
+    Tight on purpose: it only marks near-pure backdrop so trapped chroma pockets
+    seed the flood, while chroma-*tinted* character pixels stay outside it. Built
+    with channel point-ops (fast C), no per-pixel Python.
+    """
+    from PIL import ImageChops
+
+    r, g, b, _a = image.split()
+    kr, kg, kb = key
+    return ImageChops.darker(
+        ImageChops.darker(
+            r.point(lambda v: 255 if abs(v - kr) <= tol else 0),
+            g.point(lambda v: 255 if abs(v - kg) <= tol else 0),
+        ),
+        b.point(lambda v: 255 if abs(v - kb) <= tol else 0),
+    )
+
+
+def remove_background(image, *, chroma_key: tuple[int, int, int] | None = None, threshold: float = 90.0):
+    """Return *image* (RGBA) with its flat background keyed out to transparent.
+
+    If the strip already has a transparent background we leave it alone; else we
+    key out *chroma_key* (or the dominant corner color when not given) via a
+    **border flood-fill**: only background-coloured pixels *connected to an edge*
+    are removed. A global color match (the old approach) punched holes in the pet
+    wherever an interior highlight happened to match the backdrop — e.g. a pug's
+    light belly against a near-white background — which then showed through as the
+    window behind. Flood-fill keeps those interior pixels because they aren't
+    reachable from the border without crossing the (non-background) pet.
+    """
+    from collections import deque
+
+    rgba = image.convert("RGBA")
+    if _has_transparency(rgba):
+        return _repair_internal_alpha_holes(rgba)
+
+    key = chroma_key or _dominant_corner_color(rgba)
+    w, h = rgba.width, rgba.height
+    px = rgba.load()
+
+    def _is_bg(x: int, y: int) -> bool:
+        r, g, b, a = px[x, y]
+        return a > _ALPHA_FLOOR and _color_distance(r, g, b, key) <= threshold
+
+    visited = bytearray(w * h)
+    queue: deque[tuple[int, int]] = deque()
+
+    # Seed from every border pixel that looks like background.
+    for x in range(w):
+        for y in (0, h - 1):
+            if _is_bg(x, y) and not visited[y * w + x]:
+                visited[y * w + x] = 1
+                queue.append((x, y))
+    for y in range(h):
+        for x in (0, w - 1):
+            if _is_bg(x, y) and not visited[y * w + x]:
+                visited[y * w + x] = 1
+                queue.append((x, y))
+
+    # Trapped pockets: background enclosed by the character (the magenta between
+    # an arm and the body) isn't border-reachable, so also seed the flood from
+    # interior near-key pixels. Gated to a *saturated* key (our magenta backdrop)
+    # so we never seed from a character sharing a desaturated near-white/gray key
+    # — that's the hole-punching the border-only flood exists to avoid.
+    if max(key) - min(key) >= 120:
+        for i, near in enumerate(_near_key_mask(rgba, key).getdata()):
+            if near and not visited[i]:
+                visited[i] = 1
+                queue.append((i % w, i // w))
+
+    while queue:
+        x, y = queue.popleft()
+        px[x, y] = (0, 0, 0, 0)
+        for nx, ny in ((x + 1, y), (x - 1, y), (x, y + 1), (x, y - 1)):
+            if 0 <= nx < w and 0 <= ny < h:
+                idx = ny * w + nx
+                if not visited[idx]:
+                    visited[idx] = 1
+                    if _is_bg(nx, ny):
+                        queue.append((nx, ny))
+    return rgba
+
+
+def _repair_internal_alpha_holes(image):
+    """Fill transparent islands fully enclosed by opaque sprite pixels.
+
+    Some providers return "transparent" PNGs with swiss-cheese alpha inside the
+    character. Border flood-fill cannot see those because there is no opaque
+    backdrop to key, so repair the alpha mask itself: transparent components that
+    touch an image edge remain background; transparent components enclosed by
+    the sprite are filled with the average color of their opaque neighbours.
+    """
+    from collections import deque
+
+    rgba = image.convert("RGBA")
+    w, h = rgba.size
+    px = rgba.load()
+    visited = bytearray(w * h)
+
+    def _is_transparent(x: int, y: int) -> bool:
+        return px[x, y][3] <= _ALPHA_FLOOR
+
+    def _mark_border_component(sx: int, sy: int) -> None:
+        queue: deque[tuple[int, int]] = deque([(sx, sy)])
+        visited[sy * w + sx] = 1
+        while queue:
+            x, y = queue.popleft()
+            for nx, ny in ((x + 1, y), (x - 1, y), (x, y + 1), (x, y - 1)):
+                if 0 <= nx < w and 0 <= ny < h:
+                    idx = ny * w + nx
+                    if not visited[idx] and _is_transparent(nx, ny):
+                        visited[idx] = 1
+                        queue.append((nx, ny))
+
+    # First mark true background: all transparent pixels reachable from the edge.
+    for x in range(w):
+        for y in (0, h - 1):
+            if _is_transparent(x, y) and not visited[y * w + x]:
+                _mark_border_component(x, y)
+    for y in range(h):
+        for x in (0, w - 1):
+            if _is_transparent(x, y) and not visited[y * w + x]:
+                _mark_border_component(x, y)
+
+    def _collect_hole(sx: int, sy: int) -> list[tuple[int, int]]:
+        queue: deque[tuple[int, int]] = deque([(sx, sy)])
+        visited[sy * w + sx] = 1
+        pixels: list[tuple[int, int]] = []
+        while queue:
+            x, y = queue.popleft()
+            pixels.append((x, y))
+            for nx, ny in ((x + 1, y), (x - 1, y), (x, y + 1), (x, y - 1)):
+                if 0 <= nx < w and 0 <= ny < h:
+                    idx = ny * w + nx
+                    if not visited[idx] and _is_transparent(nx, ny):
+                        visited[idx] = 1
+                        queue.append((nx, ny))
+        return pixels
+
+    def _fill_color(hole: list[tuple[int, int]]) -> tuple[int, int, int, int]:
+        samples: list[tuple[int, int, int]] = []
+        seen = set(hole)
+        for x, y in hole:
+            for nx, ny in ((x + 1, y), (x - 1, y), (x, y + 1), (x, y - 1)):
+                if 0 <= nx < w and 0 <= ny < h and (nx, ny) not in seen:
+                    r, g, b, a = px[nx, ny]
+                    if a > _ALPHA_FLOOR:
+                        samples.append((r, g, b))
+        if not samples:
+            return (0, 0, 0, 255)
+        return (
+            round(sum(c[0] for c in samples) / len(samples)),
+            round(sum(c[1] for c in samples) / len(samples)),
+            round(sum(c[2] for c in samples) / len(samples)),
+            255,
+        )
+
+    for start, _ in enumerate(visited):
+        if visited[start]:
+            continue
+        x = start % w
+        y = start // w
+        if not _is_transparent(x, y):
+            continue
+        hole = _collect_hole(x, y)
+        color = _fill_color(hole)
+        for hx, hy in hole:
+            px[hx, hy] = color
+    return rgba
+
+
+# ───────────────────────── frame extraction ─────────────────────────
+
+
+def _fit_to_cell(image):
+    """Crop to content, scale to fit a padded cell, and center on transparent."""
+    from PIL import Image
+
+    target = Image.new("RGBA", (CELL_WIDTH, CELL_HEIGHT), (0, 0, 0, 0))
+    image = _drop_side_bleed(image)
+    bbox = image.getbbox()
+    if bbox is None:
+        return target
+
+    sprite = image.crop(bbox)
+    max_w = CELL_WIDTH - _CELL_PAD
+    max_h = CELL_HEIGHT - _CELL_PAD
+    scale = min(max_w / sprite.width, max_h / sprite.height, 1.0)
+    if scale != 1.0:
+        sprite = sprite.resize(
+            (max(1, round(sprite.width * scale)), max(1, round(sprite.height * scale))),
+            Image.Resampling.LANCZOS,
+        )
+    left = (CELL_WIDTH - sprite.width) // 2
+    top = (CELL_HEIGHT - sprite.height) // 2
+    target.alpha_composite(sprite, (left, top))
+    return target
+
+
+def _drop_side_bleed(image):
+    """Remove tiny separated left/right lobes before fitting a frame.
+
+    Frogger showed the failure mode: a good centered pose plus a thin vertical
+    sliver from the neighbouring pose. By the time it reaches a cell, that sliver
+    may be close enough to the subject that component extraction already grouped
+    it. A horizontal alpha projection still reveals it as a small side lobe with
+    a low mass compared to the main silhouette. Drop only those low-mass lobes;
+    keep large lobes so wide poses and real limbs survive.
+    """
+    from PIL import Image
+
+    rgba = image.convert("RGBA")
+    w, h = rgba.size
+    profile = _column_profile(rgba)  # mean alpha per column (fast C resize)
+
+    segments: list[tuple[int, int, int]] = []  # (left, right, mass)
+    start = mass = 0
+    started = False
+    for x, v in enumerate(profile + [0]):
+        if v > 2:
+            if not started:
+                start, mass, started = x, 0, True
+            mass += v
+        elif started:
+            segments.append((start, x, mass))
+            started = False
+
+    if len(segments) < 2:
+        return rgba
+    keep_mass = max(m for _, _, m in segments) * _SIDE_LOBE_RATIO
+    keep = [(l, r) for l, r, m in segments if m >= keep_mass]
+    if len(keep) == len(segments):
+        return rgba
+
+    # Zero every column band that isn't a kept segment (box paste, not per-pixel).
+    rgba = rgba.copy()
+    cut, prev = Image.new("RGBA", (w, h), (0, 0, 0, 0)), 0
+    for left, right in keep:
+        if left > prev:
+            rgba.paste(cut.crop((prev, 0, left, h)), (prev, 0))
+        prev = right
+    if prev < w:
+        rgba.paste(cut.crop((prev, 0, w, h)), (prev, 0))
+    return rgba
+
+
+def _connected_components(image) -> list[dict]:
+    """Flood-fill the alpha mask into connected blobs (4-connectivity)."""
+    alpha = image.getchannel("A")
+    w, h = image.size
+    data = alpha.tobytes()
+    visited = bytearray(w * h)
+    out: list[dict] = []
+
+    for start, a in enumerate(data):
+        if a <= _ALPHA_FLOOR or visited[start]:
+            continue
+        stack = [start]
+        visited[start] = 1
+        pixels: list[int] = []
+        min_x = w
+        min_y = h
+        max_x = 0
+        max_y = 0
+        while stack:
+            cur = stack.pop()
+            pixels.append(cur)
+            x = cur % w
+            y = cur // w
+            min_x = min(min_x, x)
+            min_y = min(min_y, y)
+            max_x = max(max_x, x)
+            max_y = max(max_y, y)
+            for nb, ok in (
+                (cur - 1, x > 0),
+                (cur + 1, x + 1 < w),
+                (cur - w, y > 0),
+                (cur + w, y + 1 < h),
+            ):
+                if ok and not visited[nb] and data[nb] > _ALPHA_FLOOR:
+                    visited[nb] = 1
+                    stack.append(nb)
+        out.append(
+            {
+                "pixels": pixels,
+                "area": len(pixels),
+                "bbox": (min_x, min_y, max_x + 1, max_y + 1),
+                "center_x": (min_x + max_x + 1) / 2,
+            }
+        )
+    return out
+
+
+def _sever_expected_gutters(strip, frame_count: int):
+    """Cut thin vertical gutters at expected frame boundaries before labeling.
+
+    Generated rows often have a shared shadow, glow, motion smear, or 1px bridge
+    that connects neighbouring poses. Component detection then sees one giant
+    blob and either fails or falls back to slot slicing. We know the requested
+    frame count, so cut a very narrow transparent band at each expected boundary
+    before connected-component labeling. If a pose truly overlaps the boundary,
+    losing a few pixels is better than exporting merged frames.
+    """
+    if frame_count <= 1:
+        return strip
+
+    out = strip.copy()
+    px = out.load()
+    slot = out.width / frame_count
+    half = max(2, min(8, round(slot * 0.02)))
+    for i in range(1, frame_count):
+        x = round(i * slot)
+        left = max(0, x - half)
+        right = min(out.width, x + half + 1)
+        for gx in range(left, right):
+            for gy in range(out.height):
+                r, g, b, _a = px[gx, gy]
+                px[gx, gy] = (r, g, b, 0)
+    return out
+
+
+def _segmentable(strip, frame_count: int) -> bool:
+    """True if the (gutter-severed) strip yields ≥ *frame_count* distinct blobs.
+
+    Used only as a quality gate: a row that can't show this many separable poses
+    is a bad generation (caller retries / falls back), never silently sliced into
+    merged frames.
+    """
+    components = _connected_components(strip)
+    if not components:
+        return False
+    largest = max(c["area"] for c in components)
+    seed_threshold = max(120, largest * 0.20)
+    return sum(1 for c in components if c["area"] >= seed_threshold) >= frame_count
+
+
+def _slot_crops(strip, frame_count: int) -> list:
+    """Slice *strip* into *frame_count* uniform columns (one coordinate space).
+
+    Equal-width columns keep every frame in a single shared coordinate frame, so
+    a later union-crop + shared placement (:func:`normalize_cells`) preserves the
+    row's real motion without the per-frame re-centering that makes a pet visibly
+    slide. Neighbour side-bleed is trimmed per column.
+    """
+    w0 = max(1, strip.width // frame_count)
+    h = strip.height
+    return [_drop_side_bleed(strip.crop((i * w0, 0, i * w0 + w0, h))) for i in range(frame_count)]
+
+
+def extract_strip_frames(
+    strip,
+    frame_count: int,
+    *,
+    chroma_key: tuple[int, int, int] | None = None,
+    method: str = "auto",
+    fit: bool = True,
+) -> list:
+    """Turn one generated row strip into *frame_count* frames.
+
+    Background is keyed out, the expected frame gutters are severed, then the
+    strip is sliced into equal columns. Connected components only *validate* that
+    the row holds *frame_count* separable poses (``components`` raises, ``auto``
+    falls back to slicing the un-severed strip).
+
+    *fit* (default) fits+centers each frame into a 192x208 cell — the standalone
+    contract for callers that don't normalize. Hatching passes ``fit=False`` to
+    keep raw, coordinate-aligned columns for :func:`normalize_cells`, which lays
+    one shared scale + baseline across the whole pet (no slide, no size pulse).
+    """
+    from PIL import Image
+
+    if isinstance(strip, (str, Path)):
+        with Image.open(strip) as opened:
+            strip = opened.convert("RGBA")
+    else:
+        strip = strip.convert("RGBA")
+
+    strip = remove_background(strip, chroma_key=chroma_key)
+    severed = _sever_expected_gutters(strip, frame_count)
+    segmentable = _segmentable(severed, frame_count)
+    if method == "components" and not segmentable:
+        raise ValueError(f"could not segment {frame_count} sprites from strip")
+
+    frames = _slot_crops(severed if segmentable else strip, frame_count)
+    return [_fit_to_cell(f) for f in frames] if fit else frames
+
+
+def _column_profile(image) -> list[int]:
+    """Per-column alpha mass — collapse the frame to a 1px-tall strip (fast in C)."""
+    from PIL import Image
+
+    return list(image.getchannel("A").resize((image.width, 1), Image.BILINEAR).getdata())
+
+
+def _best_shift(ref: list[int], prof: list[int], window: int) -> int:
+    """Integer dx that best aligns *prof* onto *ref* by cross-correlation.
+
+    This is 1-D phase correlation: the body is the dominant mass in the column
+    profile, so the peak overlap locks onto the body and a flipping arm/cape (a
+    small secondary bump) doesn't move the match. Proven on the jitter case to
+    cut body drift from ~9px to ~1px where a centroid/bbox anchor cannot.
+    """
+    n = len(ref)
+    best_score: float | None = None
+    best = 0
+    for d in range(-window, window + 1):
+        score = 0
+        for x in range(max(0, d), min(n, n + d)):
+            score += ref[x] * prof[x - d]
+        if best_score is None or score > best_score:
+            best_score = score
+            best = d
+    return best
+
+
+def normalize_cells(frames_by_state: dict[str, list], *, pad: int = _NORMALIZE_PAD) -> dict[str, list]:
+    """Register every frame into a 192x208 cell — the deterministic anti-jitter math.
+
+    A per-frame "crop→scale→center" pipeline jitters because a moving limb/cape
+    shifts the bbox (or even the centroid) and a per-frame scale pulses the size.
+    The rigorous fix, matching image-registration practice (phase correlation)
+    and AI-sprite pipelines (perfectpixel-studio / sprite-gen):
+
+    1. **Cross-correlate** each frame's column profile against the per-state
+       *median* profile to find the integer shift that locks the **body** in
+       place — robust to limbs/cape because the body dominates the profile.
+    2. **Union-crop** the registered frames through one shared window and apply
+       **one shared scale** + bottom-anchor, so size and baseline are uniform and
+       intra-state vertical motion (a jump's lift) is preserved.
+    """
+    from PIL import Image
+
+    blank = lambda: Image.new("RGBA", (CELL_WIDTH, CELL_HEIGHT), (0, 0, 0, 0))
+
+    out: dict[str, list] = {}
+    for state, frames in frames_by_state.items():
+        rgba = [f.convert("RGBA") for f in frames]
+        if not any(f.getbbox() for f in rgba):
+            out[state] = [blank() for _ in frames]
+            continue
+
+        # Pad every frame to a common canvas so column profiles are comparable.
+        w0 = max(f.width for f in rgba)
+        h0 = max(f.height for f in rgba)
+        canvas = []
+        for f in rgba:
+            if f.size != (w0, h0):
+                c = Image.new("RGBA", (w0, h0), (0, 0, 0, 0))
+                c.alpha_composite(f, (0, 0))
+                f = c
+            canvas.append(f)
+
+        # Register horizontally: shift each frame to lock the body (xcorr).
+        profiles = [_column_profile(f) for f in canvas]
+        ref = [sorted(p[x] for p in profiles)[len(profiles) // 2] for x in range(w0)]
+        window = max(8, w0 // 5)
+        margin = window
+        aligned = []
+        for f, prof in zip(canvas, profiles):
+            shifted = Image.new("RGBA", (w0 + 2 * margin, h0), (0, 0, 0, 0))
+            shifted.alpha_composite(f, (margin + _best_shift(ref, prof, window), 0))
+            aligned.append(shifted)
+
+        # Shared window + scale over the registered set; bottom-anchored, centered.
+        boxes = [b for b in (a.getbbox() for a in aligned) if b]
+        left = min(b[0] for b in boxes)
+        top = min(b[1] for b in boxes)
+        right = max(b[2] for b in boxes)
+        bottom = max(b[3] for b in boxes)
+        uw, uh = right - left, bottom - top
+        scale = min((CELL_WIDTH - pad) / uw, (CELL_HEIGHT - pad) / uh)
+        sw, sh = max(1, round(uw * scale)), max(1, round(uh * scale))
+        px, py = round((CELL_WIDTH - sw) / 2), round((CELL_HEIGHT - pad // 2) - sh)
+
+        cells = []
+        for a in aligned:
+            crop = a.crop((left, top, right, bottom))
+            if crop.size != (sw, sh):
+                crop = crop.resize((sw, sh), Image.Resampling.LANCZOS)
+            cell = blank()
+            cell.alpha_composite(crop, (px, py))
+            cells.append(cell)
+        out[state] = cells
+    return out
+
+
+# ───────────────────────── atlas composition ─────────────────────────
+
+
+def single_frame(image, *, fit: bool = True):
+    """One frame from a standalone image (e.g. the base look).
+
+    Used as an idle fallback so a pet always renders even if the idle row
+    generation failed. *fit* yields a finished 192x208 cell; ``fit=False`` yields
+    the raw keyed sprite for :func:`normalize_cells` to place with the rest.
+    """
+    from PIL import Image
+
+    if isinstance(image, (str, Path)):
+        with Image.open(image) as opened:
+            image = opened.convert("RGBA")
+    keyed = remove_background(image)
+    return _fit_to_cell(keyed) if fit else _drop_side_bleed(keyed)
+
+
+def _clear_transparent_rgb(image):
+    """Zero the RGB of fully-transparent pixels (no colored-halo residue)."""
+    from PIL import Image
+
+    rgba = image.convert("RGBA")
+    data = bytearray(rgba.tobytes())
+    for i in range(0, len(data), 4):
+        if data[i + 3] == 0:
+            data[i] = data[i + 1] = data[i + 2] = 0
+    return Image.frombytes("RGBA", rgba.size, bytes(data))
+
+
+def mirror_frames(frames: list) -> list:
+    """Horizontally flip each frame *in place* (RGBA-safe).
+
+    Used to derive ``running-left`` from an approved ``running-right`` row. The
+    flip is per-frame so the leftward loop preserves the rightward loop's frame
+    order and timing — this is NOT a whole-strip reverse (which would play the
+    animation backwards), matching the petdex/Codex mirror rule.
+    """
+    from PIL import Image
+
+    flip = getattr(Image, "Transpose", Image).FLIP_LEFT_RIGHT
+    return [frame.convert("RGBA").transpose(flip) for frame in frames]
+
+
+def compose_atlas(frames_by_state: dict[str, list]):
+    """Pack per-state frame lists into the Hermes atlas (RGBA, residue-cleared).
+
+    Missing/short states leave their trailing cells transparent; extra frames
+    beyond a state's spec are dropped.
+    """
+    from PIL import Image
+
+    atlas = Image.new("RGBA", (ATLAS_WIDTH, ATLAS_HEIGHT), (0, 0, 0, 0))
+    for state, row, count in ROW_SPECS:
+        frames = frames_by_state.get(state) or []
+        for col, frame in enumerate(frames[:count]):
+            cell = frame.convert("RGBA")
+            if cell.size != (CELL_WIDTH, CELL_HEIGHT):
+                cell = _fit_to_cell(cell)
+            atlas.alpha_composite(cell, (col * CELL_WIDTH, row * CELL_HEIGHT))
+    return _clear_transparent_rgb(atlas)
+
+
+def atlas_to_webp_bytes(atlas) -> bytes:
+    """Encode an atlas image to lossless WebP bytes (the on-disk pet format)."""
+    buf = io.BytesIO()
+    atlas.save(buf, format="WEBP", lossless=True, quality=100, method=6, exact=True)
+    return buf.getvalue()
+
+
+def validate_atlas(atlas) -> dict:
+    """Check geometry, per-cell occupancy, and transparency invariants.
+
+    Returns ``{ok, width, height, errors, warnings, filled_states}``. Errors are
+    blockers (wrong size, empty used cell, opaque/dirty transparency); warnings
+    are soft (a whole state row blank — generation likely dropped a row).
+    """
+    from PIL import Image
+
+    if isinstance(atlas, (str, Path)):
+        with Image.open(atlas) as opened:
+            atlas = opened.convert("RGBA")
+    else:
+        atlas = atlas.convert("RGBA")
+
+    errors: list[str] = []
+    warnings: list[str] = []
+
+    if atlas.size != (ATLAS_WIDTH, ATLAS_HEIGHT):
+        errors.append(f"expected {ATLAS_WIDTH}x{ATLAS_HEIGHT}, got {atlas.width}x{atlas.height}")
+        return {"ok": False, "width": atlas.width, "height": atlas.height, "errors": errors, "warnings": warnings, "filled_states": []}
+
+    filled_states: list[str] = []
+    for state, row, count in ROW_SPECS:
+        row_pixels = 0
+        for col in range(count):
+            left = col * CELL_WIDTH
+            top = row * CELL_HEIGHT
+            cell = atlas.crop((left, top, left + CELL_WIDTH, top + CELL_HEIGHT))
+            nonblank = sum(cell.getchannel("A").histogram()[1:])
+            row_pixels += nonblank
+        if row_pixels > 0:
+            filled_states.append(state)
+        else:
+            warnings.append(f"state '{state}' has no frames")
+
+    if not filled_states:
+        errors.append("atlas is empty — no state produced any frames")
+
+    # Transparent pixels must carry zero RGB (no halo residue).
+    data = atlas.tobytes()
+    residue = 0
+    for i in range(0, len(data), 4):
+        if data[i + 3] == 0 and (data[i] or data[i + 1] or data[i + 2]):
+            residue += 1
+    if residue:
+        errors.append(f"{residue} transparent pixels retain RGB residue")
+
+    return {
+        "ok": not errors,
+        "width": atlas.width,
+        "height": atlas.height,
+        "errors": errors,
+        "warnings": warnings,
+        "filled_states": filled_states,
+    }
diff --git a/agent/pet/generate/imagegen.py b/agent/pet/generate/imagegen.py
new file mode 100644
index 00000000000..1e01592e4bf
--- /dev/null
+++ b/agent/pet/generate/imagegen.py
@@ -0,0 +1,176 @@
+"""Thin image-generation layer for pet sprites.
+
+Wraps the active :class:`~agent.image_gen_provider.ImageGenProvider` with the
+two things sprite generation needs that the agent-facing ``image_generate`` tool
+doesn't expose: **N variants** (loop) and **reference-image grounding** (so each
+animation row stays the same character as the chosen base).
+
+Reference grounding only works on providers that support it — currently OpenAI
+``gpt-image-2`` (image edits) and Krea (style references). We resolve to one of
+those and surface a clear, actionable error otherwise rather than silently
+producing an ungrounded, drifting pet.
+"""
+
+from __future__ import annotations
+
+import logging
+from dataclasses import dataclass
+from pathlib import Path
+
+logger = logging.getLogger(__name__)
+
+# Providers that can ground generation on a reference image.
+# openrouter / nous reach Gemini Flash Image (and friends) over the
+# OpenRouter-compatible chat-completions image protocol, which accepts
+# reference images for grounding. Nous Portal proxies OpenRouter, so both
+# qualify.
+_REF_CAPABLE = ("openai", "openai-codex", "krea", "openrouter", "nous")
+
+
+class GenerationError(RuntimeError):
+    """Raised on any image-generation failure (no provider, API error, IO)."""
+
+
+@dataclass(frozen=True)
+class SpriteProvider:
+    """Resolved provider plus whether it can take reference images."""
+
+    name: str
+    provider: object
+    supports_references: bool
+
+
+def _discover() -> None:
+    try:
+        from hermes_cli.plugins import _ensure_plugins_discovered
+
+        _ensure_plugins_discovered()
+    except Exception as exc:  # noqa: BLE001 - discovery is best-effort
+        logger.debug("image-gen plugin discovery failed: %s", exc)
+
+
+def resolve_provider(*, require_references: bool = True) -> SpriteProvider:
+    """Pick the image provider to use for sprite work.
+
+    Preference: the configured provider when it's reference-capable, else the
+    first available reference-capable provider. With *require_references* off we
+    fall back to any available provider (used for prompt-only base drafts).
+    """
+    _discover()
+    from agent.image_gen_registry import get_active_provider, get_provider
+
+    # Configured / active provider first.
+    active = None
+    try:
+        active = get_active_provider()
+    except Exception:  # noqa: BLE001
+        active = None
+    if active is not None:
+        name = getattr(active, "name", "")
+        if name in _REF_CAPABLE and active.is_available():
+            return SpriteProvider(name=name, provider=active, supports_references=True)
+
+    # Any available reference-capable provider.
+    for name in _REF_CAPABLE:
+        provider = get_provider(name)
+        if provider is not None and provider.is_available():
+            return SpriteProvider(name=name, provider=provider, supports_references=True)
+
+    if not require_references and active is not None and active.is_available():
+        return SpriteProvider(
+            name=getattr(active, "name", "unknown"), provider=active, supports_references=False
+        )
+
+    raise GenerationError(
+        "Pet generation needs an image backend that supports reference images. "
+        "Open `hermes tools` → Image Generation and configure OpenRouter, Nous "
+        "Portal, or OpenAI (gpt-image-2) with an API key."
+    )
+
+
+def _save_local(image_ref: str, *, prefix: str) -> Path:
+    """Return a local path for *image_ref*, downloading it if it's a URL."""
+    if image_ref.startswith(("http://", "https://")):
+        from agent.image_gen_provider import save_url_image
+
+        return Path(save_url_image(image_ref, prefix=prefix))
+    return Path(image_ref)
+
+
+def _rejected_background(error: str) -> bool:
+    """True when a provider error is specifically about the ``background`` param.
+
+    Transparent backgrounds are a per-model capability (e.g. some gpt-image tiers
+    reject ``background=transparent`` outright). We detect that one rejection so
+    we can retry without the flag rather than failing the whole pet — our chroma
+    key pass makes the result transparent regardless.
+    """
+    lowered = (error or "").lower()
+    return "background" in lowered and ("not supported" in lowered or "transparent" in lowered)
+
+
+def generate(
+    prompt: str,
+    *,
+    n: int = 1,
+    reference_images: list[Path] | None = None,
+    provider: SpriteProvider | None = None,
+    prefix: str = "pet_gen",
+) -> list[Path]:
+    """Generate *n* square sprite images and return their local paths.
+
+    *reference_images* grounds the output on a base image (required for rows).
+    We *ask* for a transparent background, but fall back to an opaque generation
+    (cleaned up downstream by the chroma-key pass) on models that reject the
+    flag. Raises :class:`GenerationError` if nothing usable comes back.
+    """
+    sprite = provider or resolve_provider(require_references=bool(reference_images))
+    if reference_images and not sprite.supports_references:
+        raise GenerationError(
+            f"image backend '{sprite.name}' cannot use reference images; "
+            "configure OpenAI gpt-image-2 or Krea for pet generation"
+        )
+
+    refs = [str(p) for p in (reference_images or [])]
+
+    def _run(extra: dict) -> tuple[Path | None, str]:
+        kwargs: dict = {"aspect_ratio": "square", **extra}
+        if refs:
+            # Providers disagree on the ref kwarg name: our OpenRouter/Nous
+            # backends read ``reference_images``, OpenAI's gpt-image-2 reads
+            # ``reference_image_urls``. Send both; each ignores the other.
+            kwargs["reference_images"] = refs
+            kwargs["reference_image_urls"] = refs
+        try:
+            result = sprite.provider.generate(prompt, **kwargs)
+        except Exception as exc:  # noqa: BLE001 - normalize provider crashes
+            logger.debug("provider.generate crashed: %s", exc)
+            return None, str(exc)
+        if not isinstance(result, dict) or not result.get("success"):
+            return None, (result or {}).get("error", "unknown error") if isinstance(result, dict) else "no result"
+        image_ref = result.get("image")
+        if not image_ref:
+            return None, "provider returned no image"
+        try:
+            return _save_local(str(image_ref), prefix=prefix), ""
+        except Exception as exc:  # noqa: BLE001
+            return None, f"could not save generated image: {exc}"
+
+    out: list[Path] = []
+    last_error = ""
+    allow_transparent = True
+    for _ in range(max(1, n)):
+        path, err = _run({"background": "transparent"} if allow_transparent else {})
+        # Model doesn't support the transparent flag → drop it for this and every
+        # remaining variant (no point re-probing a capability we just disproved).
+        if path is None and allow_transparent and _rejected_background(err):
+            allow_transparent = False
+            path, err = _run({})
+        if path is not None:
+            out.append(path)
+        else:
+            last_error = err
+
+    if not out:
+        raise GenerationError(last_error or "image generation produced no output")
+    return out
diff --git a/agent/pet/generate/orchestrate.py b/agent/pet/generate/orchestrate.py
new file mode 100644
index 00000000000..238c490a22a
--- /dev/null
+++ b/agent/pet/generate/orchestrate.py
@@ -0,0 +1,292 @@
+"""Pet generation orchestration — the base-draft → hatch flow.
+
+Two steps, mirroring the UX across every surface:
+
+1. :func:`generate_base_drafts` — a handful of prompt-only "what should this pet
+   look like" variants. Cheap; the user picks one (or retries for a fresh set).
+2. :func:`hatch_pet` — takes the chosen base and generates one grounded row
+   strip per Hermes state, slices each into frames, composes the atlas, validates
+   it, and writes the pet into the store.
+
+Splitting it this way bounds cost (4 cheap base calls per round; the ~6 row
+calls happen once, on the pet you actually keep) and gives each UI a natural
+preview/loading point.
+"""
+
+from __future__ import annotations
+
+import logging
+import time
+from concurrent.futures import ThreadPoolExecutor, as_completed
+from dataclasses import dataclass
+from pathlib import Path
+from typing import Callable
+
+from agent.pet.generate import atlas, imagegen, prompts
+from agent.pet.generate.imagegen import GenerationError, SpriteProvider
+
+logger = logging.getLogger(__name__)
+
+# (event, detail) — e.g. ("row", "idle"), ("compose", ""), ("save", "<slug>").
+ProgressFn = Callable[[str, str], None]
+
+# Image generations are independent network calls, so we fan them out instead of
+# blocking on each in turn — a hatch is ~8 row calls that would otherwise run
+# back-to-back and routinely blow past the client's RPC timeout. Capped so we
+# don't hammer the provider's rate limit (one cold call can still be slow).
+_MAX_PARALLEL_GENERATIONS = 4
+_MIN_FILLED_STATES = 6
+_REQUIRED_STATES = frozenset({"idle", "running-right", "waving"})
+
+
+@dataclass(frozen=True)
+class HatchResult:
+    """Outcome of a successful :func:`hatch_pet`."""
+
+    slug: str
+    display_name: str
+    spritesheet: Path
+    states: list[str]
+    validation: dict
+
+
+def _harden_transparency(path: Path) -> Path:
+    """Key out any solid backdrop the provider painted; save as an RGBA PNG.
+
+    ``background=transparent`` is requested on every call, but image models honor
+    it inconsistently — some still paint a flat (often near-white) backdrop. We
+    run the same chroma-key pass the row extractor uses so every base draft the
+    user picks between (and the reference the rows are grounded on) is a clean
+    cutout. Best-effort: a decode failure leaves the original untouched.
+    """
+    from PIL import Image
+
+    try:
+        with Image.open(path) as opened:
+            keyed = atlas.remove_background(opened.convert("RGBA"))
+        # Zero the RGB of any leftover semi-transparent edge pixels so a keyed
+        # draft has no colored halo when composited on the dark UI.
+        keyed = atlas._clear_transparent_rgb(keyed)
+        out = path.with_suffix(".png")
+        keyed.save(out, format="PNG")
+        return out
+    except Exception as exc:  # noqa: BLE001 - cosmetic; fall back to the raw image
+        logger.debug("base draft transparency hardening failed for %s: %s", path, exc)
+        return path
+
+
+def generate_base_drafts(
+    concept: str,
+    *,
+    n: int = 4,
+    style: str = "auto",
+    provider: SpriteProvider | None = None,
+    on_draft: Callable[[int, Path], None] | None = None,
+    is_cancelled: Callable[[], bool] | None = None,
+) -> list[Path]:
+    """Generate *n* candidate base looks for *concept*; returns image paths.
+
+    Each draft is hardened to a transparent cutout (see :func:`_harden_transparency`).
+    Drafts are generated concurrently and *on_draft(index, path)* fires as each
+    one finishes (not at the end) so callers can stream previews to the UI
+    instead of leaving it blank until the whole batch is done.
+
+    *is_cancelled*, when supplied, is polled cooperatively: a draft that hasn't
+    started yet is skipped, and once it trips we stop staging/streaming further
+    drafts and cancel any queued work (already-in-flight provider calls can't be
+    hard-killed, but their results are dropped).
+    """
+    sprite = provider or imagegen.resolve_provider(require_references=False)
+    cancelled = is_cancelled or (lambda: False)
+
+    # Each draft is its own one-shot generation, run concurrently so the user
+    # waits for one image, not N. A single draft failing must not sink the set.
+    # Each gets a distinct variation nudge so the options aren't near-duplicates.
+    logger.info("pet generate: drafting %d base looks for %r (style=%s)", n, concept, style)
+
+    def _one(index: int) -> tuple[int, Path | None]:
+        if cancelled():
+            return index, None
+        t0 = time.monotonic()
+        variation = prompts.BASE_VARIATIONS[index % len(prompts.BASE_VARIATIONS)]
+        prompt = prompts.build_base_prompt(concept, style=style, variation=variation)
+        try:
+            out = imagegen.generate(prompt, n=1, provider=sprite, prefix="pet_base")
+        except Exception as exc:  # noqa: BLE001 - tolerate a single failed draft
+            logger.warning("pet generate: draft %d failed after %.1fs: %s", index, time.monotonic() - t0, exc)
+            return index, None
+        if not out:
+            logger.warning("pet generate: draft %d produced no image", index)
+            return index, None
+        logger.info("pet generate: draft %d ready in %.1fs", index, time.monotonic() - t0)
+        return index, _harden_transparency(out[0])
+
+    workers = max(1, min(n, _MAX_PARALLEL_GENERATIONS))
+    results: dict[int, Path] = {}
+    with ThreadPoolExecutor(max_workers=workers) as pool:
+        futures = [pool.submit(_one, i) for i in range(n)]
+        # as_completed runs in *this* (the caller's) thread, so on_draft — and any
+        # gateway event it emits — inherits the request's bound transport, unlike
+        # the worker threads above.
+        for fut in as_completed(futures):
+            if cancelled():
+                logger.info("pet generate: cancelled — dropping remaining drafts")
+                for pending in futures:
+                    pending.cancel()
+                break
+            index, path = fut.result()
+            if path is None:
+                continue
+            results[index] = path
+            if on_draft is not None:
+                try:
+                    on_draft(index, path)
+                except Exception as exc:  # noqa: BLE001 - progress is best-effort
+                    logger.debug("on_draft callback failed: %s", exc)
+
+    drafts = [results[i] for i in sorted(results)]
+    if not drafts and not cancelled():
+        raise GenerationError("image generation produced no usable drafts")
+    return drafts
+
+
+def hatch_pet(
+    *,
+    base_image: str | Path,
+    slug: str,
+    display_name: str = "",
+    description: str = "",
+    concept: str = "",
+    style: str = "auto",
+    on_progress: ProgressFn | None = None,
+    provider: SpriteProvider | None = None,
+    is_cancelled: Callable[[], bool] | None = None,
+) -> HatchResult:
+    """Turn an approved base image into a full, installed Hermes pet.
+
+    Generates a grounded row strip per state, extracts frames, composes +
+    validates the atlas, and registers it. The idle row falls back to the base
+    look so the pet always renders. Raises :class:`GenerationError` on failure.
+
+    *is_cancelled*, when supplied, is polled cooperatively: rows that haven't
+    started are skipped, queued rows are cancelled, and once every row is done we
+    abort (raising :class:`GenerationError`) before composing/saving so a stopped
+    hatch never writes a half-built pet.
+    """
+    base = Path(base_image)
+    if not base.is_file():
+        raise GenerationError(f"base image not found: {base}")
+
+    sprite = provider or imagegen.resolve_provider(require_references=True)
+    progress = on_progress or (lambda *_: None)
+    cancelled = is_cancelled or (lambda: False)
+    label = concept or display_name or slug
+
+    frames_by_state: dict[str, list] = {}
+    total_rows = len(atlas.ROW_SPECS)
+    logger.info("pet hatch %r: generating %d animation rows", slug, total_rows)
+
+    # Generate every state's row strip concurrently — they're independent
+    # grounded calls, so the hatch waits for the slowest row, not their sum. A
+    # single row failing is tolerated (idle is guaranteed below).
+    def _gen_row(spec: tuple[str, int, int]) -> tuple[str, list | None]:
+        state, _row, count = spec
+        if cancelled():
+            return state, None
+        t0 = time.monotonic()
+        try:
+            strips = imagegen.generate(
+                prompts.build_row_prompt(state, count, label, style=style),
+                n=1,
+                reference_images=[base],
+                provider=sprite,
+                prefix=f"pet_row_{state}",
+            )
+            # One image call per row (the expensive part). ``auto`` validates by
+            # connected components with an equal-slot fallback; raw (fit=False) so
+            # normalize_cells registers the whole pet at once. We deliberately do
+            # NOT re-generate a ragged row — the registration pass salvages it far
+            # cheaper than another image-model round-trip.
+            frames = atlas.extract_strip_frames(strips[0], count, method="auto", fit=False)
+            logger.info("pet hatch %r: row %r ready in %.1fs", slug, state, time.monotonic() - t0)
+            return state, frames
+        except Exception as exc:  # noqa: BLE001 - one bad row is tolerated (idle guaranteed)
+            logger.warning("pet hatch %r: row %r failed after %.1fs: %s", slug, state, time.monotonic() - t0, exc)
+            return state, None
+
+    # running-left is derived by mirroring running-right (guaranteed-consistent
+    # and one fewer generation), so we don't generate it directly.
+    generated_specs = [spec for spec in atlas.ROW_SPECS if spec[0] != "running-left"]
+
+    workers = max(1, min(len(generated_specs), _MAX_PARALLEL_GENERATIONS))
+    done = 0
+    with ThreadPoolExecutor(max_workers=workers) as pool:
+        futures = [pool.submit(_gen_row, spec) for spec in generated_specs]
+        # as_completed runs on the caller (request) thread, so progress events
+        # emitted here inherit the request transport — unlike the worker threads.
+        for fut in as_completed(futures):
+            if cancelled():
+                logger.info("pet hatch %r: cancelled — dropping remaining rows", slug)
+                for pending in futures:
+                    pending.cancel()
+                break
+            state, frames = fut.result()
+            done += 1
+            progress("row", f"{state}:{done}:{total_rows}")
+            if frames:
+                frames_by_state[state] = frames
+
+    if cancelled():
+        raise GenerationError("hatch cancelled")
+
+    # Derive running-left from the approved running-right row (per-frame mirror,
+    # preserving order/timing). Missing running-right is rejected below; a pet
+    # without its canonical walk cycle is a failed hatch, not a shippable mascot.
+    right = frames_by_state.get("running-right")
+    if right:
+        done += 1
+        progress("row", f"running-left:{done}:{total_rows}")
+        frames_by_state["running-left"] = atlas.mirror_frames(right)
+        logger.info("pet hatch %r: row 'running-left' mirrored from running-right", slug)
+    else:
+        logger.warning("pet hatch %r: no running-right to mirror; left walk left empty", slug)
+
+    # Idle is the resting state the renderer falls back to — guarantee it.
+    if not frames_by_state.get("idle"):
+        progress("row", "idle-fallback")
+        frames_by_state["idle"] = [atlas.single_frame(base, fit=False)]
+
+    progress("compose", "")
+    logger.info("pet hatch %r: composing atlas from %d states", slug, len(frames_by_state))
+    # One shared scale + baseline across every state so the pet never slides or
+    # pulses size between frames; compose just packs the normalized cells.
+    sheet = atlas.compose_atlas(atlas.normalize_cells(frames_by_state))
+    validation = atlas.validate_atlas(sheet)
+    if not validation["ok"]:
+        raise GenerationError("; ".join(validation["errors"]) or "atlas validation failed")
+    filled_states = set(validation["filled_states"])
+    missing_required = sorted(_REQUIRED_STATES - filled_states)
+    if missing_required:
+        raise GenerationError(f"missing required animation row(s): {', '.join(missing_required)}")
+    if len(filled_states) < _MIN_FILLED_STATES:
+        raise GenerationError(
+            f"only {len(filled_states)}/{len(atlas.ROW_SPECS)} animation rows were usable; regenerate"
+        )
+
+    from agent.pet import store
+
+    progress("save", slug)
+    logger.info("pet hatch %r: saving pet", slug)
+    pet = store.register_local_pet(
+        sheet,
+        slug=slug,
+        display_name=display_name or slug,
+        description=description,
+    )
+    return HatchResult(
+        slug=pet.slug,
+        display_name=pet.display_name,
+        spritesheet=pet.spritesheet,
+        states=validation["filled_states"],
+        validation=validation,
+    )
diff --git a/agent/pet/generate/prompts.py b/agent/pet/generate/prompts.py
new file mode 100644
index 00000000000..c6afbc28313
--- /dev/null
+++ b/agent/pet/generate/prompts.py
@@ -0,0 +1,140 @@
+"""Prompt builders for pet generation.
+
+Two prompt shapes: a *base* prompt (prompt-only, produces the canonical look the
+user picks between) and per-*state* *row* prompts (grounded on the chosen base,
+produce one horizontal strip of N poses). Prompts stay concise and
+sprite-production oriented; the identity lock and "one transparent row" framing
+matter more than flowery description.
+
+We generate the full petdex/Codex nine-state set (see
+:data:`agent.pet.generate.atlas.ROW_SPECS`) so a hatched pet is a valid
+``petdex submit`` spritesheet.
+"""
+
+from __future__ import annotations
+
+# What each petdex/Codex state should depict (kept short — these go straight into
+# the row prompt). Phrased to avoid the common sprite-gen failure modes (detached
+# effects, motion lines, shadows). Critical distinction: ``running`` is the
+# *working* state (in place), while ``running-right`` / ``running-left`` are the
+# actual directional walk/run cycles.
+STATE_ACTIONS: dict[str, str] = {
+    "idle": "a calm idle loop: subtle breathing, a tiny blink or gentle bob, no big gestures",
+    "running-right": (
+        "a sideways walk/run locomotion cycle moving to the RIGHT: the character "
+        "faces and travels right with clear directional steps, a smooth gait loop"
+    ),
+    "running-left": (
+        "a sideways walk/run locomotion cycle moving to the LEFT: the character "
+        "faces and travels left with clear directional steps (the mirror of the "
+        "right-facing run)"
+    ),
+    "waving": "a friendly greeting: raising a paw/hand/limb to wave, clear up-and-down gesture",
+    "jumping": "a happy celebration jump: anticipation, lift off the ground, peak, and land",
+    "failed": "a sad or deflated reaction: slumped, dejected, small frown — readable but not noisy",
+    "waiting": (
+        "an expectant 'waiting on you' pose: looking up/out as if asking for input "
+        "or approval — distinct from idle and review"
+    ),
+    "running": (
+        "focused active work, staying IN PLACE (NOT walking or foot-running): "
+        "leaning in, concentrating, busy 'thinking / processing / typing' energy"
+    ),
+    "review": "careful inspection: a focused lean, head tilt, studying something intently",
+}
+
+_STYLE_HINTS: dict[str, str] = {
+    # Default to the popular petdex look: crisp 16-bit PIXEL ART, not the smooth
+    # 2D illustration (let alone 3D render) gpt-image reaches for by default.
+    "auto": (
+        " Style: crisp 16-bit PIXEL-ART game sprite — visible square pixels, a small "
+        "limited palette, clean dark outline, flat cel shading, chunky chibi "
+        "proportions, like a classic SNES/JRPG party member or a petdex.dev mascot. "
+        "Absolutely NOT 3D-rendered, NOT a smooth painted or vector illustration, "
+        "NOT photorealistic — no soft gradients, no realistic lighting, no figurine look."
+    ),
+    "pixel": " Render in clean 16-bit pixel-art style with visible square pixels and a limited palette.",
+    "plush": " Render as a soft plush toy.",
+    "clay": " Render as a claymation / soft 3D clay figure.",
+    "sticker": " Render as a glossy die-cut sticker.",
+    "flat-vector": " Render in flat vector mascot style.",
+    "3d-toy": " Render as a glossy 3D toy.",
+    "painterly": " Render in a soft painterly style.",
+}
+
+_BACKGROUND = (
+    "Center one full-body character on a flat, uniform, high-contrast chroma-key "
+    "background (prefer pure hot magenta #FF00FF unless that color appears on "
+    "the character). The background must completely surround the character: one "
+    "even color with NO gradient, vignette, texture, pattern, scenery, shadow, "
+    "ground line, frame, or border, so it keys out cleanly. The background color "
+    "must not appear anywhere on the character itself. No text, no labels."
+)
+
+
+def style_hint(style: str | None) -> str:
+    return _STYLE_HINTS.get((style or "auto").strip().lower(), "")
+
+
+# Per-draft nudges so the 4 base options are actually distinct — gpt-image returns
+# near-duplicates for a single prompt. We vary the *look* (palette, build,
+# expression, accents), NOT the pose, so the chosen base still grounds clean,
+# consistent animation rows.
+BASE_VARIATIONS: tuple[str, ...] = (
+    "",
+    "a distinctly different colour palette and markings",
+    "rounder, chunkier chibi proportions and a bigger head",
+    "a different face and expression, with unique accent/accessory details",
+    "a leaner, taller build and an alternate colour scheme",
+    "bolder, more saturated colours and a playful expression",
+)
+
+
+def build_base_prompt(concept: str, *, style: str | None = "auto", variation: str = "") -> str:
+    """The base look: a single, clean, centered full-body mascot.
+
+    *variation* differentiates one draft from the next (see :data:`BASE_VARIATIONS`).
+    """
+    concept = (concept or "a cute friendly mascot creature").strip()
+    nudge = f" Make this design distinct: {variation}." if variation else ""
+    return (
+        f"A cute, characterful mascot pet: {concept}. "
+        "Compact, whole-body silhouette that reads clearly at small size, "
+        "appealing face, simple consistent palette. "
+        # A neutral, symmetric, at-rest stance makes the cleanest identity anchor
+        "Neutral front-facing standing pose, upright and symmetric, arms/limbs "
+        "relaxed at the sides, feet together on the ground, any cape/accessories "
+        "hanging straight and still."
+        f"{nudge} "
+        f"{_BACKGROUND}{style_hint(style)}"
+    )
+
+
+def build_row_prompt(state: str, frame_count: int, concept: str, *, style: str | None = "auto") -> str:
+    """A row strip: *frame_count* poses of the SAME character, left→right.
+
+    The attached base image is the identity source of truth; the prompt locks
+    species, palette, face, and props to it.
+    """
+    action = STATE_ACTIONS.get(state, "a simple idle pose")
+    concept = (concept or "the mascot").strip()
+    return (
+        f"Using the attached reference image as the exact same character "
+        f"(same species, face, colors, markings, proportions, and props), "
+        f"draw a single horizontal strip of {frame_count} animation frames showing {action}. "
+        f"The {frame_count} poses must be evenly spaced left to right, each fully separated "
+        "by clear empty chroma-key gutters; silhouettes must NEVER touch, overlap, "
+        "share a shadow, share a ground line, share motion trails, or merge into "
+        "one connected shape. "
+        # Registration: a clean sprite sheet keeps the character locked in place
+        # so only the action moves — this is what stops the loop sliding/pulsing.
+        "REGISTRATION (critical): the character is the SAME height and SAME width "
+        "in every frame, drawn at the SAME scale, centered over the SAME point, "
+        "with all feet resting on ONE shared horizontal ground line across the "
+        "whole strip. Keep the body's center, size, and stance fixed frame to "
+        "frame — ONLY the limbs/features the action needs may move. Capes, cloaks, "
+        "bags, and scarves stay in the SAME place and shape every frame (no "
+        "swinging, flowing, or drifting) unless the action itself requires it. No "
+        "pose is cropped at the strip edges. "
+        f"{_BACKGROUND}{style_hint(style)}"
+    )
diff --git a/agent/pet/manifest.py b/agent/pet/manifest.py
index 94d539691dc..98a0e4a3f7e 100644
--- a/agent/pet/manifest.py
+++ b/agent/pet/manifest.py
@@ -21,6 +21,7 @@ Read-only and unauthenticated; no credentials involved.
 from __future__ import annotations
 
 import logging
+import threading
 import time
 from dataclasses import dataclass
 
@@ -28,7 +29,7 @@ logger = logging.getLogger(__name__)
 
 MANIFEST_URL = "https://petdex.dev/api/manifest"
 
-_DEFAULT_TIMEOUT = 20.0
+_DEFAULT_TIMEOUT = 10.0
 
 # In-process cache for the (large, slow, identical-per-call) manifest. The list
 # is a static CDN object that barely changes, yet a single session can ask for
@@ -38,6 +39,9 @@ _DEFAULT_TIMEOUT = 20.0
 _MANIFEST_TTL = 300.0
 _cache: tuple[float, list[ManifestEntry]] | None = None
 
+_prefetch_lock = threading.Lock()
+_prefetching = False
+
 
 def clear_cache() -> None:
     """Drop the cached manifest (forces the next fetch to hit the network)."""
@@ -45,6 +49,39 @@ def clear_cache() -> None:
     _cache = None
 
 
+def _cache_is_warm() -> bool:
+    return _cache is not None and time.monotonic() - _cache[0] < _MANIFEST_TTL
+
+
+def prefetch(*, timeout: float = _DEFAULT_TIMEOUT) -> None:
+    """Warm the manifest cache in a daemon thread — idempotent, never blocks.
+
+    The desktop picker calls this when it loads the (instant) local-only gallery
+    so the full petdex catalog is usually cached by the time it's requested,
+    without ever holding up the user's own pets on a network round-trip.
+    """
+    global _prefetching
+
+    if _cache_is_warm():
+        return
+
+    with _prefetch_lock:
+        if _prefetching:
+            return
+        _prefetching = True
+
+    def _run() -> None:
+        global _prefetching
+        try:
+            fetch_manifest(timeout=timeout)
+        except Exception as exc:  # noqa: BLE001 - best-effort warm
+            logger.debug("petdex manifest prefetch failed: %s", exc)
+        finally:
+            _prefetching = False
+
+    threading.Thread(target=_run, name="petdex-prefetch", daemon=True).start()
+
+
 @dataclass(frozen=True)
 class ManifestEntry:
     """A single pet's row in the manifest."""
diff --git a/agent/pet/store.py b/agent/pet/store.py
index 8f9f8376865..42627c1ac81 100644
--- a/agent/pet/store.py
+++ b/agent/pet/store.py
@@ -18,6 +18,7 @@ from __future__ import annotations
 
 import json
 import logging
+import re
 from dataclasses import dataclass
 from pathlib import Path
 
@@ -41,11 +42,16 @@ class InstalledPet:
     description: str
     directory: Path
     spritesheet: Path
+    created_by: str = ""  # "generator" for pets hatched locally; "" for petdex installs
 
     @property
     def exists(self) -> bool:
         return self.spritesheet.is_file()
 
+    @property
+    def generated(self) -> bool:
+        return self.created_by == "generator"
+
 
 def pets_dir() -> Path:
     """Return the profile-scoped pets directory (created on demand)."""
@@ -113,6 +119,7 @@ def load_pet(slug: str) -> InstalledPet | None:
         description=str(meta.get("description", "") or ""),
         directory=directory,
         spritesheet=_resolve_spritesheet(directory, meta),
+        created_by=str(meta.get("createdBy", "") or ""),
     )
 
 
@@ -197,6 +204,101 @@ def install_pet(slug: str, *, force: bool = False, timeout: float = _DOWNLOAD_TI
     return pet
 
 
+def slugify(name: str) -> str:
+    """Lowercase, hyphenate, and strip a display name into a filesystem slug."""
+    slug = re.sub(r"[^a-z0-9]+", "-", (name or "").strip().lower()).strip("-")
+    return slug or "pet"
+
+
+def unique_slug(name: str) -> str:
+    """A :func:`slugify` result that doesn't collide with an existing pet dir."""
+    base = slugify(name)
+    slug = base
+    counter = 2
+    while (pets_dir() / slug).exists():
+        slug = f"{base}-{counter}"
+        counter += 1
+    return slug
+
+
+def _write_spritesheet(source, dest: Path) -> None:
+    """Write *source* (PIL image, bytes, or path) as a lossless WebP at *dest*."""
+    if isinstance(source, (bytes, bytearray)):
+        dest.write_bytes(bytes(source))
+        return
+
+    from PIL import Image
+
+    if isinstance(source, (str, Path)):
+        with Image.open(source) as opened:
+            image = opened.convert("RGBA")
+    else:
+        image = source.convert("RGBA")
+    image.save(dest, format="WEBP", lossless=True, quality=100, method=6, exact=True)
+
+
+def register_local_pet(
+    spritesheet,
+    *,
+    slug: str,
+    display_name: str = "",
+    description: str = "",
+) -> InstalledPet:
+    """Write a locally-generated pet into the store and return it.
+
+    *spritesheet* may be a PIL image, raw WebP/PNG bytes, or a path. The pet
+    appears in :func:`installed_pets` immediately, and because :func:`install_pet`
+    returns an already-on-disk pet before consulting the manifest, it can be
+    adopted (``pet.select`` / ``/pet <slug>``) without a manifest entry.
+    """
+    slug = slugify(slug)
+    directory = pets_dir() / slug
+    directory.mkdir(parents=True, exist_ok=True)
+    sprite_path = directory / "spritesheet.webp"
+    try:
+        _write_spritesheet(spritesheet, sprite_path)
+    except Exception as exc:  # noqa: BLE001 - normalize to one error type
+        raise PetStoreError(f"could not write spritesheet for '{slug}': {exc}") from exc
+
+    meta = {
+        "id": slug,
+        "displayName": display_name or slug,
+        "description": description or "",
+        "spritesheetPath": sprite_path.name,
+        "createdBy": "generator",
+    }
+    (directory / "pet.json").write_text(json.dumps(meta, indent=2), encoding="utf-8")
+
+    pet = load_pet(slug)
+    if pet is None or not pet.exists:
+        raise PetStoreError(f"register of generated pet '{slug}' did not produce a spritesheet")
+    return pet
+
+
+def export_pet(slug: str) -> tuple[str, bytes]:
+    """Zip an installed pet's folder (pet.json + spritesheet) → (filename, bytes).
+
+    Dotfiles (cached thumbs, backups) are skipped so the archive is a clean,
+    re-importable pet package. Raises :class:`PetStoreError` if not installed.
+    """
+    import io
+    import zipfile
+
+    root = pets_dir()
+    directory = root / slug.strip()
+    # Guard against traversal: the target must be a direct child of pets_dir.
+    if directory.resolve().parent != root.resolve() or not directory.is_dir():
+        raise PetStoreError(f"pet '{slug}' is not installed")
+
+    name = directory.name
+    buf = io.BytesIO()
+    with zipfile.ZipFile(buf, "w", zipfile.ZIP_DEFLATED) as archive:
+        for path in sorted(directory.iterdir()):
+            if path.is_file() and not path.name.startswith("."):
+                archive.write(path, f"{name}/{path.name}")
+    return f"{name}.zip", buf.getvalue()
+
+
 _THUMB_FRAME_W = 192
 _THUMB_FRAME_H = 208
 _THUMB_W = 96  # rendered ~40px; 2x+ keeps it crisp on HiDPI
@@ -301,6 +403,15 @@ def remove_pet(slug: str) -> bool:
     slug = _safe_slug(slug)
     if not slug:
         return False
+
+    # The cached thumbnail lives in pets/.thumbs/<slug>.png — OUTSIDE the pet
+    # dir, so rmtree won't catch it. Drop it too, or a later pet that reuses this
+    # slug renders this one's stale thumbnail.
+    try:
+        (_thumbs_dir() / f"{slug}.png").unlink(missing_ok=True)
+    except OSError:
+        pass
+
     directory = pets_dir() / slug
     if not directory.is_dir():
         return False
@@ -308,6 +419,55 @@ def remove_pet(slug: str) -> bool:
     return not directory.exists()
 
 
+def rename_pet(slug: str, display_name: str) -> str | None:
+    """Rename a pet's ``displayName`` AND realign its slug/dir to match.
+
+    Generated pets are hatched under a provisional, prompt-derived slug; when
+    the user names the pet on the reveal screen we make that name the real
+    identity so lists/subtitles show what they typed, not the prompt. The dir is
+    renamed to ``slugify(name)`` (and the cached thumbnail moved alongside it)
+    whenever that yields a free, different slug — otherwise the slug is left as
+    is. Returns the resulting slug on success, or ``None`` on failure.
+    """
+    slug = _safe_slug(slug)
+    display_name = (display_name or "").strip()
+    if not slug or not display_name:
+        return None
+    directory = pets_dir() / slug
+    pet_json = directory / "pet.json"
+    if not pet_json.is_file():
+        return None
+    try:
+        meta = json.loads(pet_json.read_text(encoding="utf-8"))
+    except (OSError, ValueError):
+        meta = {}
+    if not isinstance(meta, dict):
+        meta = {}
+    meta["displayName"] = display_name
+
+    new_slug = slug
+    desired = slugify(display_name)
+    if desired and desired != slug and not (pets_dir() / desired).exists():
+        try:
+            directory.rename(pets_dir() / desired)
+            try:
+                (_thumbs_dir() / f"{slug}.png").rename(_thumbs_dir() / f"{desired}.png")
+            except OSError:
+                pass
+            directory = pets_dir() / desired
+            pet_json = directory / "pet.json"
+            new_slug = desired
+            meta["id"] = new_slug
+        except OSError:
+            new_slug = slug  # keep the provisional slug if the move fails
+
+    try:
+        pet_json.write_text(json.dumps(meta, indent=2), encoding="utf-8")
+    except OSError:
+        return None
+    return new_slug
+
+
 def _download(url: str, dest: Path, *, timeout: float) -> None:
     import httpx
 
diff --git a/tests/agent/test_pet_generate.py b/tests/agent/test_pet_generate.py
new file mode 100644
index 00000000000..1a3ad424bb8
--- /dev/null
+++ b/tests/agent/test_pet_generate.py
@@ -0,0 +1,413 @@
+"""Tests for pet generation: deterministic atlas ops, store register, orchestration.
+
+No network/API calls — image generation is mocked with synthetic strips so the
+whole pipeline (segmentation → compose → validate → register → adopt) is
+exercised hermetically.
+"""
+
+from __future__ import annotations
+
+import pytest
+
+from agent.pet.generate import atlas
+
+PIL = pytest.importorskip("PIL")
+from PIL import Image, ImageDraw  # noqa: E402
+
+
+def _strip(n_blobs: int, *, transparent: bool = True, bg=(0, 255, 0, 255), size=(208, 208)) -> Image.Image:
+    """A horizontal strip with *n_blobs* clearly-separated colored ellipses."""
+    w = size[0] * n_blobs
+    h = size[1]
+    base = (0, 0, 0, 0) if transparent else bg
+    img = Image.new("RGBA", (w, h), base)
+    draw = ImageDraw.Draw(img)
+    for i in range(n_blobs):
+        cx = i * size[0] + size[0] // 2
+        cy = h // 2
+        r = size[0] // 3
+        color = (40 + i * 30 % 200, 80, 200 - i * 20 % 180, 255)
+        draw.ellipse((cx - r, cy - r, cx + r, cy + r), fill=color)
+    return img
+
+
+# ───────────────────────── frame extraction ─────────────────────────
+
+
+def test_extract_strip_frames_transparent_returns_centered_cells():
+    frames = atlas.extract_strip_frames(_strip(6), 6)
+    assert len(frames) == 6
+    for frame in frames:
+        assert frame.size == (atlas.CELL_WIDTH, atlas.CELL_HEIGHT)
+        # Background corners must be transparent.
+        assert frame.getpixel((0, 0))[3] == 0
+        # Something is drawn.
+        assert frame.getchannel("A").getextrema()[1] > 0
+
+
+def test_extract_strip_frames_keys_out_solid_background():
+    frames = atlas.extract_strip_frames(_strip(4, transparent=False), 4)
+    assert len(frames) == 4
+    # The green backdrop must be gone (corner transparent).
+    assert frames[0].getpixel((0, 0))[3] == 0
+
+
+def test_remove_background_clears_trapped_chroma_pocket():
+    # Green body enclosing a magenta pocket (the "pink between the arm" case):
+    # the pocket isn't border-reachable, so it must be cleared by interior seeding.
+    img = Image.new("RGBA", (200, 200), (255, 0, 255, 255))  # magenta backdrop
+    draw = ImageDraw.Draw(img)
+    draw.ellipse((40, 40, 160, 160), fill=(40, 200, 60, 255))  # body
+    draw.ellipse((85, 85, 115, 115), fill=(255, 0, 255, 255))  # trapped pocket
+    keyed = atlas.remove_background(img)
+    assert keyed.getpixel((100, 100))[3] == 0  # pocket cleared
+    assert keyed.getpixel((100, 50))[3] > 0  # body still opaque
+    assert keyed.getpixel((2, 2))[3] == 0  # border cleared
+
+
+def test_extract_strip_frames_repairs_provider_alpha_holes():
+    img = _strip(1)
+    draw = ImageDraw.Draw(img)
+    cx = img.width // 2
+    cy = img.height // 2
+    draw.ellipse((cx - 16, cy - 16, cx + 16, cy + 16), fill=(0, 0, 0, 0))
+
+    frames = atlas.extract_strip_frames(img, 1, method="components")
+    assert frames[0].getpixel((atlas.CELL_WIDTH // 2, atlas.CELL_HEIGHT // 2))[3] > 0
+
+
+def test_extract_strip_frames_severs_thin_bridges_between_frames():
+    # AI strips often connect poses with a 1px shadow/glow bridge. Strict
+    # component extraction must still find each frame instead of treating the row
+    # as one merged subject.
+    img = _strip(4)
+    draw = ImageDraw.Draw(img)
+    draw.line((20, img.height // 2, img.width - 20, img.height // 2), fill=(255, 255, 255, 255), width=1)
+
+    frames = atlas.extract_strip_frames(img, 4, method="components")
+    assert len(frames) == 4
+    assert all(frame.getchannel("A").getextrema()[1] > 0 for frame in frames)
+
+
+def test_extract_strip_frames_drops_small_side_lobes_from_adjacent_frames():
+    # Frogger regression: a real pose plus a small separated side lobe from a
+    # neighbouring pose. The side lobe should not survive into the fitted cell.
+    img = Image.new("RGBA", (atlas.CELL_WIDTH, atlas.CELL_HEIGHT), (0, 0, 0, 0))
+    draw = ImageDraw.Draw(img)
+    draw.ellipse((52, 34, 150, 188), fill=(70, 190, 70, 255))
+    draw.rectangle((4, 70, 24, 160), fill=(70, 190, 70, 255))
+    draw.rectangle((168, 82, 186, 150), fill=(70, 190, 70, 255))
+
+    frame = atlas.extract_strip_frames(img, 1, method="components")[0]
+    alpha = frame.getchannel("A")
+    left_edge_mass = sum(1 for x in range(0, 36) for y in range(frame.height) if alpha.getpixel((x, y)) > 16)
+    right_edge_mass = sum(1 for x in range(frame.width - 36, frame.width) for y in range(frame.height) if alpha.getpixel((x, y)) > 16)
+    assert left_edge_mass == 0
+    assert right_edge_mass == 0
+
+
+def test_extract_strip_frames_slot_fallback_when_unsegmentable():
+    # A single connected smear can't be split into 5 components → slot fallback.
+    img = Image.new("RGBA", (200 * 5, 208), (0, 0, 0, 0))
+    ImageDraw.Draw(img).rectangle((0, 80, 200 * 5 - 1, 120), fill=(200, 50, 50, 255))
+    frames = atlas.extract_strip_frames(img, 5, method="auto")
+    assert len(frames) == 5
+
+
+def test_extract_components_method_raises_when_too_few():
+    img = Image.new("RGBA", (400, 208), (0, 0, 0, 0))
+    ImageDraw.Draw(img).ellipse((10, 10, 100, 100), fill=(255, 0, 0, 255))
+    with pytest.raises(ValueError):
+        atlas.extract_strip_frames(img, 6, method="components")
+
+
+# ───────────────────────── atlas compose / validate ─────────────────────────
+
+
+def _frames_for_all_states() -> dict[str, list]:
+    out: dict[str, list] = {}
+    for state, _row, count in atlas.ROW_SPECS:
+        out[state] = atlas.extract_strip_frames(_strip(count), count)
+    return out
+
+
+def test_compose_atlas_geometry_and_validation():
+    sheet = atlas.compose_atlas(_frames_for_all_states())
+    assert sheet.size == (atlas.ATLAS_WIDTH, atlas.ATLAS_HEIGHT)
+    result = atlas.validate_atlas(sheet)
+    assert result["ok"], result["errors"]
+    assert set(result["filled_states"]) == {s for s, _, _ in atlas.ROW_SPECS}
+
+
+def test_compose_atlas_leaves_unused_tail_transparent():
+    # waving has 4 frames; columns 4 and 5 of its row must be transparent.
+    sheet = atlas.compose_atlas(_frames_for_all_states())
+    wave_row = next(r for s, r, _ in atlas.ROW_SPECS if s == "waving")
+    top = wave_row * atlas.CELL_HEIGHT
+    for col in (4, 5):
+        left = col * atlas.CELL_WIDTH
+        cell = sheet.crop((left, top, left + atlas.CELL_WIDTH, top + atlas.CELL_HEIGHT))
+        assert cell.getchannel("A").getextrema()[1] == 0
+
+
+def test_validate_atlas_rejects_wrong_size():
+    bad = Image.new("RGBA", (100, 100), (0, 0, 0, 0))
+    result = atlas.validate_atlas(bad)
+    assert not result["ok"]
+    assert any("expected" in e for e in result["errors"])
+
+
+def test_validate_atlas_rejects_rgb_residue():
+    sheet = atlas.compose_atlas(_frames_for_all_states())
+    # Poke a fully-transparent pixel with non-zero RGB.
+    sheet.putpixel((0, 0), (120, 0, 0, 0))
+    result = atlas.validate_atlas(sheet)
+    assert not result["ok"]
+    assert any("residue" in e for e in result["errors"])
+
+
+def test_validate_atlas_warns_on_empty_state():
+    frames = _frames_for_all_states()
+    frames["jumping"] = []
+    sheet = atlas.compose_atlas(frames)
+    result = atlas.validate_atlas(sheet)
+    assert result["ok"]  # one empty row is a warning, not an error
+    assert any("jumping" in w for w in result["warnings"])
+
+
+def test_single_frame_fits_cell():
+    frame = atlas.single_frame(_strip(1))
+    assert frame.size == (atlas.CELL_WIDTH, atlas.CELL_HEIGHT)
+    assert frame.getchannel("A").getextrema()[1] > 0
+
+
+# ───────────────────────── store register / adopt ─────────────────────────
+
+
+def test_slugify_and_unique_slug():
+    from agent.pet import store
+
+    assert store.slugify("My Cool Pet!") == "my-cool-pet"
+    assert store.slugify("   ") == "pet"
+    first = store.unique_slug("Robo")
+    (store.pets_dir() / first).mkdir(parents=True)
+    assert store.unique_slug("Robo") == "robo-2"
+
+
+def test_register_local_pet_appears_and_is_adoptable():
+    from agent.pet import store
+
+    sheet = atlas.compose_atlas(_frames_for_all_states())
+    pet = store.register_local_pet(sheet, slug="Sparky", display_name="Sparky", description="zappy")
+    assert pet.slug == "sparky"
+    assert pet.exists
+    assert any(p.slug == "sparky" for p in store.installed_pets())
+
+    # install_pet returns the on-disk pet without ever hitting the manifest.
+    adopted = store.install_pet("sparky")
+    assert adopted.slug == "sparky"
+    assert adopted.display_name == "Sparky"
+
+
+def test_register_local_pet_is_generated_and_exports_zip():
+    import io
+    import zipfile
+
+    from agent.pet import store
+
+    sheet = atlas.compose_atlas(_frames_for_all_states())
+    store.register_local_pet(sheet, slug="zippy", display_name="Zippy")
+    assert store.load_pet("zippy").generated is True  # createdBy=generator
+
+    filename, data = store.export_pet("zippy")
+    assert filename == "zippy.zip"
+    names = zipfile.ZipFile(io.BytesIO(data)).namelist()
+    assert "zippy/pet.json" in names
+    assert any(n.startswith("zippy/spritesheet") for n in names)
+
+
+def test_export_pet_rejects_unknown_and_traversal():
+    from agent.pet import store
+
+    with pytest.raises(store.PetStoreError):
+        store.export_pet("does-not-exist")
+    with pytest.raises(store.PetStoreError):
+        store.export_pet("../secrets")
+
+
+def test_register_local_pet_accepts_bytes():
+    from agent.pet import store
+
+    sheet = atlas.compose_atlas(_frames_for_all_states())
+    data = atlas.atlas_to_webp_bytes(sheet)
+    pet = store.register_local_pet(data, slug="bytey")
+    assert pet.exists
+
+
+# ───────────────────────── orchestration (mocked imagegen) ─────────────────────────
+
+
+def test_generate_base_drafts_returns_n(monkeypatch, tmp_path):
+    from agent.pet.generate import imagegen, orchestrate
+
+    calls = {"n": 0}
+
+    def fake_generate(prompt, *, n=1, reference_images=None, provider=None, prefix="pet"):
+        paths = []
+        for i in range(n):
+            calls["n"] += 1
+            p = tmp_path / f"{prefix}_{calls['n']}.png"
+            _strip(1).save(p)
+            paths.append(p)
+        return paths
+
+    monkeypatch.setattr(imagegen, "resolve_provider", lambda **_: object())
+    monkeypatch.setattr(imagegen, "generate", fake_generate)
+
+    drafts = orchestrate.generate_base_drafts("a fox", n=4)
+    assert len(drafts) == 4
+
+
+def test_generate_base_drafts_hardens_opaque_background(monkeypatch, tmp_path):
+    """A provider that ignores background=transparent still yields a cutout."""
+    from agent.pet.generate import imagegen, orchestrate
+
+    def fake_generate(prompt, *, n=1, reference_images=None, provider=None, prefix="pet"):
+        # Solid-green backdrop with a blob — i.e. the provider painted a backdrop.
+        p = tmp_path / f"{prefix}_opaque.png"
+        _strip(1, transparent=False, bg=(0, 255, 0, 255)).save(p)
+        return [p]
+
+    monkeypatch.setattr(imagegen, "resolve_provider", lambda **_: object())
+    monkeypatch.setattr(imagegen, "generate", fake_generate)
+
+    drafts = orchestrate.generate_base_drafts("a fox", n=1)
+    assert len(drafts) == 1
+
+    with Image.open(drafts[0]) as out:
+        rgba = out.convert("RGBA")
+    # The keyed backdrop is now transparent (corner pixel fully see-through).
+    assert rgba.getpixel((0, 0))[3] == 0
+    # The pet blob in the center is still opaque.
+    assert rgba.getpixel((rgba.width // 2, rgba.height // 2))[3] > 0
+
+
+def test_hatch_pet_end_to_end(monkeypatch, tmp_path):
+    from agent.pet import store
+    from agent.pet.generate import atlas as atlas_mod
+    from agent.pet.generate import imagegen, orchestrate
+
+    base = tmp_path / "base.png"
+    _strip(1).save(base)
+
+    def fake_generate(prompt, *, n=1, reference_images=None, provider=None, prefix="pet"):
+        # Return a synthetic row strip; frame count is inferable from the spec.
+        state = prefix.replace("pet_row_", "")
+        count = atlas_mod.FRAME_COUNTS.get(state, 6)
+        p = tmp_path / f"{prefix}.png"
+        _strip(count).save(p)
+        return [p]
+
+    monkeypatch.setattr(imagegen, "resolve_provider", lambda **_: object())
+    monkeypatch.setattr(imagegen, "generate", fake_generate)
+
+    events: list[tuple[str, str]] = []
+    result = orchestrate.hatch_pet(
+        base_image=base,
+        slug="mocky",
+        display_name="Mocky",
+        description="a test pet",
+        concept="a fox",
+        on_progress=lambda ev, detail: events.append((ev, detail)),
+    )
+
+    assert result.slug == "mocky"
+    assert result.validation["ok"]
+    assert set(result.states) == {s for s, _, _ in atlas_mod.ROW_SPECS}
+    assert ("compose", "") in events
+    # The pet is on disk and adoptable.
+    assert store.load_pet("mocky").exists
+
+
+def test_hatch_pet_idle_fallback_when_row_fails(monkeypatch, tmp_path):
+    from agent.pet.generate import atlas as atlas_mod
+    from agent.pet.generate import imagegen, orchestrate
+    from agent.pet.generate.imagegen import GenerationError
+
+    base = tmp_path / "base.png"
+    _strip(1).save(base)
+
+    def fake_generate(prompt, *, n=1, reference_images=None, provider=None, prefix="pet"):
+        if prefix == "pet_row_idle":
+            raise GenerationError("boom")
+        state = prefix.replace("pet_row_", "")
+        count = atlas_mod.FRAME_COUNTS.get(state, 6)
+        p = tmp_path / f"{prefix}.png"
+        _strip(count).save(p)
+        return [p]
+
+    monkeypatch.setattr(imagegen, "resolve_provider", lambda **_: object())
+    monkeypatch.setattr(imagegen, "generate", fake_generate)
+
+    result = orchestrate.hatch_pet(base_image=base, slug="fallbacky", concept="a fox")
+    assert "idle" in result.states  # filled by the base-image fallback
+
+
+def test_hatch_pet_rejects_missing_required_animation_rows(monkeypatch, tmp_path):
+    from agent.pet.generate import atlas as atlas_mod
+    from agent.pet.generate import imagegen, orchestrate
+    from agent.pet.generate.imagegen import GenerationError
+
+    base = tmp_path / "base.png"
+    _strip(1).save(base)
+
+    def fake_generate(prompt, *, n=1, reference_images=None, provider=None, prefix="pet"):
+        if prefix == "pet_row_running-right":
+            raise GenerationError("bad row")
+        state = prefix.replace("pet_row_", "")
+        count = atlas_mod.FRAME_COUNTS.get(state, 6)
+        p = tmp_path / f"{prefix}.png"
+        _strip(count).save(p)
+        return [p]
+
+    monkeypatch.setattr(imagegen, "resolve_provider", lambda **_: object())
+    monkeypatch.setattr(imagegen, "generate", fake_generate)
+
+    with pytest.raises(GenerationError, match="running-right"):
+        orchestrate.hatch_pet(base_image=base, slug="broken", concept="a fox")
+
+
+def test_resolve_provider_errors_without_backend(monkeypatch):
+    from agent.pet.generate import imagegen
+
+    monkeypatch.setattr(imagegen, "_discover", lambda: None)
+    monkeypatch.setattr("agent.image_gen_registry.get_active_provider", lambda: None)
+    monkeypatch.setattr("agent.image_gen_registry.get_provider", lambda name: None)
+
+    with pytest.raises(imagegen.GenerationError):
+        imagegen.resolve_provider(require_references=True)
+
+
+def test_generate_retries_without_transparent_background(monkeypatch, tmp_path):
+    """A model that rejects background=transparent still produces images."""
+    from agent.pet.generate import imagegen
+
+    saved = tmp_path / "img.png"
+    _strip(1).save(saved)
+    calls: list[dict] = []
+
+    class FakeProvider:
+        def generate(self, prompt, **kwargs):
+            calls.append(kwargs)
+            if kwargs.get("background") == "transparent":
+                return {"success": False, "error": "Transparent background is not supported for this model."}
+            return {"success": True, "image": str(saved)}
+
+    sprite = imagegen.SpriteProvider(name="openai", provider=FakeProvider(), supports_references=False)
+
+    out = imagegen.generate("a fox", n=2, provider=sprite)
+    assert len(out) == 2
+    # First variant probes transparent (rejected) then retries opaque; the second
+    # variant skips the transparent probe entirely.
+    backgrounds = [c.get("background") for c in calls]
+    assert backgrounds == ["transparent", None, None]