fix: close review gaps for per-model threshold overrides (#63020)

Follow-up to the salvaged contributor commit, closing the three gaps
flagged in the sweeper review:

1. Init ordering: assign compression.model_thresholds to a selected
   plugin context engine BEFORE the initial update_model() call in
   agent_init.py, so the initial model's override applies from init
   (previously it only took effect after the first /model switch).
   Base-class ContextEngine.update_model() now snapshots the
   pre-override percent once so repeated switches fall back to the
   engine's configured threshold, not a previous model's override.
2. DEFAULT_CONFIG: add compression.model_thresholds (empty map) to
   hermes_cli/config.py — additive key, no _config_version bump.
3. Docs: document the key in
   website/docs/developer-guide/context-compression-and-caching.md
   (yaml example, parameter table, dedicated section) and update the
   plugin-boundary note in context-engine-plugin.md to state the
   explicit context-engine contract for model_thresholds.

Adds tests/run_agent/test_per_model_threshold_init_ordering.py:
plugin-engine AIAgent init regression (override applies at init,
empty map unchanged), DEFAULT_CONFIG key presence, floor interaction
on the model-switch path (override below the small-context floor is
raised to the floor; above the floor wins), and base-class config
snapshot across repeated switches. Also maps @bennybuoy in
contributors/emails/.

website/docs/developer-guide/context-compression-and-caching.md

@@ -82,6 +82,9 @@ All compression settings are read from `config.yaml` under the `compression` key
 compression:
   enabled: true              # Enable/disable compression (default: true)
   threshold: 0.50            # Fraction of context window (default: 0.50 = 50%)
+  # model_thresholds:        # Per-model threshold overrides (substring match,
+  #   "glm-5.2": 0.40        # longest key wins). See "Per-model threshold
+  #   "claude-sonnet": 0.35  # overrides" below.
   target_ratio: 0.20         # How much of threshold to keep as tail (default: 0.20)
   protect_last_n: 20         # Minimum protected tail messages (default: 20)
   codex_gpt55_autoraise: true  # gpt-5.5 on Codex OAuth: raise trigger to 85% (default: true)
@@ -101,6 +104,7 @@ auxiliary:
 | Parameter | Default | Range | Description |
 |-----------|---------|-------|-------------|
 | `threshold` | `0.50` | 0.0-1.0 | Compression triggers when prompt tokens ≥ `threshold × context_length` |
+| `model_thresholds` | `{}` | map | Per-model overrides of `threshold`. Keys are substring-matched against the model name (longest match wins). The small-context floor still applies on top (see below) |
 | `target_ratio` | `0.20` | 0.10-0.80 | Controls tail protection token budget: `threshold_tokens × target_ratio` |
 | `protect_last_n` | `20` | ≥1 | Minimum number of recent messages always preserved |
 | `protect_first_n` | `3` | (hardcoded) | System prompt + first exchange always preserved |
@@ -108,6 +112,39 @@ auxiliary:
 | `codex_gpt55_autoraise_notice` | `true` | bool | Show the one-time Codex gpt-5.5 autoraise notice. Set `false` to keep the 85% autoraise but suppress the banner |
 | `codex_app_server_auto` | `native` | `native`, `hermes`, `off` | Thread-compaction mode for Codex app-server sessions (see below) |
 
+### Per-model threshold overrides
+
+`compression.model_thresholds` lets you trigger compaction at different points
+depending on the active model — useful when you swap between models with very
+different context windows (e.g. a 1M-context model can compress later while a
+128K model should compress earlier):
+
+```yaml
+compression:
+  threshold: 0.50
+  model_thresholds:
+    "glm-5.2": 0.40
+    "glm-5.2-1M": 0.25
+    "claude-sonnet": 0.35
+```
+
+Resolution rules:
+
+- Keys are **substring-matched** against the model name; the **longest
+  matching key wins** (`glm-5.2-1M` beats `glm-5.2` for model `glm-5.2-1M`).
+- When no key matches (or the map is empty), the global `threshold` applies.
+- The override is re-resolved on every `/model` switch; switching to a model
+  with no matching key falls back to the global `threshold`.
+- The **small-context floor still applies on top** of overrides (raise-only):
+  models with context windows below 512K are floored at `0.75`, so an
+  override below the floor is raised to `0.75`, while an override above it
+  (e.g. `0.80`) wins.
+
+Plugin context engines can reuse the same resolution logic via
+`from agent.context_compressor import resolve_model_threshold`; engines that
+override `update_model()` own their own compaction policy and may ignore the
+map.
+
 ### Codex gpt-5.5 threshold autoraise
 
 The ChatGPT Codex OAuth backend hard-caps gpt-5.5 at a **272K** context window

website/docs/developer-guide/context-engine-plugin.md

@@ -165,7 +165,7 @@ context:
   engine: "lcm"   # must match your engine's name property
 ```
 
-The `compression` config block (`compression.threshold`, `compression.protect_last_n`, etc.) is specific to the built-in `ContextCompressor`. Your engine should define its own config format if needed, reading from `config.yaml` during initialization.
+The `compression` config block (`compression.threshold`, `compression.protect_last_n`, etc.) is specific to the built-in `ContextCompressor`, with one explicit exception: `compression.model_thresholds` (per-model threshold overrides) is part of the context-engine contract. The host assigns the resolved map to `engine.model_thresholds` *before* the initial `update_model()` call, and the base-class `update_model()` applies it (longest substring match, falling back to the engine's configured threshold). Engines that override `update_model()` own their own compaction policy and may honor or ignore the map — `from agent.context_compressor import resolve_model_threshold` to reuse the same resolution logic. For everything else, your engine should define its own config format if needed, reading from `config.yaml` during initialization.
 
 ## Testing