hermes-agent/tools/memory_tool.py
Teknium 0dee92df22
feat(security): promptware defense — shared threat patterns + memory load-time scan + tool-result delimiters (#32269)
Hardens the context window against Brainworm-class promptware attacks
(see #496). Three changes:

1. tools/threat_patterns.py — single source of truth for injection/promptware
   patterns. Replaces the duplicated pattern lists in prompt_builder.py and
   memory_tool.py. Adds ~15 new Brainworm/C2 patterns (node registration,
   heartbeat/beacon, pull tasking, anti-forensic disk avoidance, identity
   override, known framework names). Three scopes — 'all' (narrow, classic
   injection), 'context' (adds promptware/role-play, broader detection),
   'strict' (adds persistence/SSH-backdoor patterns for user-mediated writes).

2. MemoryStore.load_from_disk() now scans entries at snapshot-build time.
   Poisoned entries are replaced with [BLOCKED: ...] placeholders in the
   frozen system-prompt snapshot. Live state keeps the original so the
   user can still inspect + remove via memory(action=read/remove). Scan is
   deterministic from disk bytes — prefix-cache invariant holds.

3. make_tool_result_message() wraps results from high-risk tools
   (web_extract, web_search, browser_*, mcp_*) in
   <untrusted_tool_result source="...">...</untrusted_tool_result>
   delimiters with framing prose telling the model the content is data,
   not instructions. Architectural defense against indirect injection
   from poisoned web pages, GitHub issues, MCP responses — does NOT
   regex-scan tool results (pattern arms race + per-iteration latency).
   Multimodal content lists pass through unwrapped to preserve adapter
   compatibility.

Pattern philosophy: anchor on C2-specific vocabulary or unambiguous attack
behavior, NOT on bossy English. Dropped patterns suggested in #496 that
would have tripped legitimate content: standalone 'you are obligated to',
'do not respond immediately', 'you must X' without a C2-verb anchor.

Validation:
- 257/257 targeted tests pass (test_threat_patterns + test_memory_tool +
  test_tool_dispatch_helpers + test_prompt_builder)
- E2E run with real Brainworm payload: blocked from AGENTS.md context-file
  path, blocked from MEMORY.md snapshot, wrapped in delimiters when
  arriving via web_extract. Legitimate 'you must follow conventions'
  phrasing not flagged.

Explicitly NOT in this PR (per #496 discussion):
- Per-tool-result regex scanning (pattern arms race)
- SessionBehaviorMonitor / polling-loop detection (wrong layer)
- Outbound network gating (Docker backend already covers this)
- security.context_scanning warn|block knob (current behavior is always
  block-with-placeholder — there's no warn mode that makes sense)

Closes #496 for Phase 1 + the architectural delimiter piece of Phase 2.
Phase 3 stays in tracking issue territory.
2026-05-25 14:52:24 -07:00

724 lines
29 KiB
Python

#!/usr/bin/env python3
"""
Memory Tool Module - Persistent Curated Memory
Provides bounded, file-backed memory that persists across sessions. Two stores:
- MEMORY.md: agent's personal notes and observations (environment facts, project
conventions, tool quirks, things learned)
- USER.md: what the agent knows about the user (preferences, communication style,
expectations, workflow habits)
Both are injected into the system prompt as a frozen snapshot at session start.
Mid-session writes update files on disk immediately (durable) but do NOT change
the system prompt -- this preserves the prefix cache for the entire session.
The snapshot refreshes on the next session start.
Entry delimiter: § (section sign). Entries can be multiline.
Character limits (not tokens) because char counts are model-independent.
Design:
- Single `memory` tool with action parameter: add, replace, remove, read
- replace/remove use short unique substring matching (not full text or IDs)
- Behavioral guidance lives in the tool schema description
- Frozen snapshot pattern: system prompt is stable, tool responses show live state
"""
import json
import logging
import os
import re
import tempfile
import time
from contextlib import contextmanager
from pathlib import Path
from hermes_constants import get_hermes_home
from typing import Dict, Any, List, Optional
from utils import atomic_replace
# fcntl is Unix-only; on Windows use msvcrt for file locking
msvcrt = None
try:
import fcntl
except ImportError:
fcntl = None
try:
import msvcrt
except ImportError:
pass
logger = logging.getLogger(__name__)
# Where memory files live — resolved dynamically so profile overrides
# (HERMES_HOME env var changes) are always respected. The old module-level
# constant was cached at import time and could go stale if a profile switch
# happened after the first import.
def get_memory_dir() -> Path:
"""Return the profile-scoped memories directory."""
return get_hermes_home() / "memories"
ENTRY_DELIMITER = "\n§\n"
# ---------------------------------------------------------------------------
# Memory content scanning — lightweight check for injection/exfiltration
# in content that gets injected into the system prompt.
#
# Patterns live in ``tools/threat_patterns.py`` — the single source of truth
# shared with the context-file scanner and the tool-result delimiter system.
# Memory uses the "strict" scope (broadest pattern set) because:
# - memory entries are user-curated; the user can rewrite a flagged entry
# - memory enters the system prompt as a FROZEN snapshot, so a poisoned
# entry persists for the entire session and across sessions until
# explicitly removed.
# ---------------------------------------------------------------------------
from tools.threat_patterns import first_threat_message as _first_threat_message
def _scan_memory_content(content: str) -> Optional[str]:
"""Scan memory content for injection/exfil patterns. Returns error string if blocked."""
return _first_threat_message(content, scope="strict")
def _drift_error(path: "Path", bak_path: str) -> Dict[str, Any]:
"""Build the error dict returned when external drift is detected.
The on-disk memory file contains content that wouldn't round-trip
through the tool's parser/serializer — flushing would discard the
appended/edited content from a patch tool, shell append, manual edit,
or sister-session write. We refuse the mutation, point the operator at
the .bak.<ts> snapshot we took, and tell them what to do next.
"""
return {
"success": False,
"error": (
f"Refusing to write {path.name}: file on disk has content that "
f"wouldn't round-trip through the memory tool (likely added by "
f"the patch tool, a shell append, a manual edit, or a "
f"concurrent session). A snapshot was saved to {bak_path}. "
f"Resolve the drift first — either rewrite the file as a clean "
f"§-delimited list of entries, or move the extra content out — "
f"then retry. This guard exists to prevent silent data loss "
f"(issue #26045)."
),
"drift_backup": bak_path,
"remediation": (
"Open the .bak file, integrate the missing entries into the "
"memory tool one at a time via memory(action=add, content=...), "
"then remove or rewrite the original file to a clean state."
),
}
class MemoryStore:
"""
Bounded curated memory with file persistence. One instance per AIAgent.
Maintains two parallel states:
- _system_prompt_snapshot: frozen at load time, used for system prompt injection.
Never mutated mid-session. Keeps prefix cache stable.
- memory_entries / user_entries: live state, mutated by tool calls, persisted to disk.
Tool responses always reflect this live state.
"""
def __init__(self, memory_char_limit: int = 2200, user_char_limit: int = 1375):
self.memory_entries: List[str] = []
self.user_entries: List[str] = []
self.memory_char_limit = memory_char_limit
self.user_char_limit = user_char_limit
# Frozen snapshot for system prompt -- set once at load_from_disk()
self._system_prompt_snapshot: Dict[str, str] = {"memory": "", "user": ""}
def load_from_disk(self):
"""Load entries from MEMORY.md and USER.md, capture system prompt snapshot.
The frozen snapshot is what enters the system prompt. We scan each
entry for injection/promptware patterns at snapshot-build time —
ANY hit replaces the entry text in the snapshot with a placeholder
like ``[BLOCKED: …]``, so a poisoned-on-disk memory file (supply
chain, compromised tool, sister-session write) cannot inject into
the system prompt.
The live ``memory_entries`` / ``user_entries`` lists keep the
original text so the user can still SEE poisoned entries via
``memory(action=read)`` and remove them — silently dropping them
would hide the attack from the user.
Scanning is deterministic from disk bytes, so the snapshot remains
stable for the entire session (prefix-cache invariant holds).
"""
mem_dir = get_memory_dir()
mem_dir.mkdir(parents=True, exist_ok=True)
self.memory_entries = self._read_file(mem_dir / "MEMORY.md")
self.user_entries = self._read_file(mem_dir / "USER.md")
# Deduplicate entries (preserves order, keeps first occurrence)
self.memory_entries = list(dict.fromkeys(self.memory_entries))
self.user_entries = list(dict.fromkeys(self.user_entries))
# Sanitize entries for the system-prompt snapshot only. Live state
# (memory_entries / user_entries) keeps the raw text so the user
# can see + remove poisoned entries via the memory tool.
sanitized_memory = self._sanitize_entries_for_snapshot(self.memory_entries, "MEMORY.md")
sanitized_user = self._sanitize_entries_for_snapshot(self.user_entries, "USER.md")
# Capture frozen snapshot for system prompt injection
self._system_prompt_snapshot = {
"memory": self._render_block("memory", sanitized_memory),
"user": self._render_block("user", sanitized_user),
}
@staticmethod
def _sanitize_entries_for_snapshot(entries: List[str], filename: str) -> List[str]:
"""Return ``entries`` with any threat-matching entry replaced by a placeholder.
Each entry is scanned with the shared threat-pattern library at the
``"strict"`` scope (same as memory writes). On match, the entry is
replaced in the returned list with ``"[BLOCKED: <filename> entry
contained threat pattern: <ids>. Removed from system prompt.]"`` —
the placeholder enters the snapshot, the original entry stays in
live state for the user to inspect and delete.
Empty or already-block-marker entries pass through unchanged.
"""
from tools.threat_patterns import scan_for_threats
sanitized: List[str] = []
for entry in entries:
if not entry or entry.startswith("[BLOCKED:"):
sanitized.append(entry)
continue
findings = scan_for_threats(entry, scope="strict")
if findings:
logger.warning(
"Memory entry from %s blocked at load time: %s",
filename, ", ".join(findings),
)
sanitized.append(
f"[BLOCKED: {filename} entry contained threat pattern(s): "
f"{', '.join(findings)}. Removed from system prompt; "
f"use memory(action=read) to inspect and memory(action=remove) "
f"to delete the original.]"
)
else:
sanitized.append(entry)
return sanitized
@staticmethod
@contextmanager
def _file_lock(path: Path):
"""Acquire an exclusive file lock for read-modify-write safety.
Uses a separate .lock file so the memory file itself can still be
atomically replaced via os.replace().
"""
lock_path = path.with_suffix(path.suffix + ".lock")
lock_path.parent.mkdir(parents=True, exist_ok=True)
if fcntl is None and msvcrt is None:
yield
return
fd = open(lock_path, "a+", encoding="utf-8")
try:
if fcntl:
fcntl.flock(fd, fcntl.LOCK_EX)
else:
fd.seek(0)
msvcrt.locking(fd.fileno(), msvcrt.LK_LOCK, 1)
yield
finally:
if fcntl:
try:
fcntl.flock(fd, fcntl.LOCK_UN)
except (OSError, IOError):
pass
elif msvcrt:
try:
fd.seek(0)
msvcrt.locking(fd.fileno(), msvcrt.LK_UNLCK, 1)
except (OSError, IOError):
pass
fd.close()
@staticmethod
def _path_for(target: str) -> Path:
mem_dir = get_memory_dir()
if target == "user":
return mem_dir / "USER.md"
return mem_dir / "MEMORY.md"
def _reload_target(self, target: str) -> Optional[str]:
"""Re-read entries from disk into in-memory state.
Called under file lock to get the latest state before mutating.
Returns the backup path if external drift was detected (the on-disk
file contains content that wouldn't round-trip through our
parser/serializer, OR an entry larger than the store's char limit).
When drift is detected the caller must abort the mutation —
flushing would discard the un-roundtrippable content.
Returns None on clean reload.
"""
path = self._path_for(target)
bak = self._detect_external_drift(target)
fresh = self._read_file(path)
fresh = list(dict.fromkeys(fresh)) # deduplicate
self._set_entries(target, fresh)
return bak
def save_to_disk(self, target: str):
"""Persist entries to the appropriate file. Called after every mutation."""
get_memory_dir().mkdir(parents=True, exist_ok=True)
self._write_file(self._path_for(target), self._entries_for(target))
def _entries_for(self, target: str) -> List[str]:
if target == "user":
return self.user_entries
return self.memory_entries
def _set_entries(self, target: str, entries: List[str]):
if target == "user":
self.user_entries = entries
else:
self.memory_entries = entries
def _char_count(self, target: str) -> int:
entries = self._entries_for(target)
if not entries:
return 0
return len(ENTRY_DELIMITER.join(entries))
def _char_limit(self, target: str) -> int:
if target == "user":
return self.user_char_limit
return self.memory_char_limit
def add(self, target: str, content: str) -> Dict[str, Any]:
"""Append a new entry. Returns error if it would exceed the char limit."""
content = content.strip()
if not content:
return {"success": False, "error": "Content cannot be empty."}
# Scan for injection/exfiltration before accepting
scan_error = _scan_memory_content(content)
if scan_error:
return {"success": False, "error": scan_error}
with self._file_lock(self._path_for(target)):
# Re-read from disk under lock to pick up writes from other sessions.
# If external drift was detected, the file was backed up to .bak.<ts>
# — refuse the mutation so we don't clobber the un-roundtrippable
# content the patch tool / shell append / sister session wrote.
bak = self._reload_target(target)
if bak:
return _drift_error(self._path_for(target), bak)
entries = self._entries_for(target)
limit = self._char_limit(target)
# Reject exact duplicates
if content in entries:
return self._success_response(target, "Entry already exists (no duplicate added).")
# Calculate what the new total would be
new_entries = entries + [content]
new_total = len(ENTRY_DELIMITER.join(new_entries))
if new_total > limit:
current = self._char_count(target)
return {
"success": False,
"error": (
f"Memory at {current:,}/{limit:,} chars. "
f"Adding this entry ({len(content)} chars) would exceed the limit. "
f"Replace or remove existing entries first."
),
"current_entries": entries,
"usage": f"{current:,}/{limit:,}",
}
entries.append(content)
self._set_entries(target, entries)
self.save_to_disk(target)
return self._success_response(target, "Entry added.")
def replace(self, target: str, old_text: str, new_content: str) -> Dict[str, Any]:
"""Find entry containing old_text substring, replace it with new_content."""
old_text = old_text.strip()
new_content = new_content.strip()
if not old_text:
return {"success": False, "error": "old_text cannot be empty."}
if not new_content:
return {"success": False, "error": "new_content cannot be empty. Use 'remove' to delete entries."}
# Scan replacement content for injection/exfiltration
scan_error = _scan_memory_content(new_content)
if scan_error:
return {"success": False, "error": scan_error}
with self._file_lock(self._path_for(target)):
bak = self._reload_target(target)
if bak:
return _drift_error(self._path_for(target), bak)
entries = self._entries_for(target)
matches = [(i, e) for i, e in enumerate(entries) if old_text in e]
if not matches:
return {"success": False, "error": f"No entry matched '{old_text}'."}
if len(matches) > 1:
# If all matches are identical (exact duplicates), operate on the first one
unique_texts = {e for _, e in matches}
if len(unique_texts) > 1:
previews = [e[:80] + ("..." if len(e) > 80 else "") for _, e in matches]
return {
"success": False,
"error": f"Multiple entries matched '{old_text}'. Be more specific.",
"matches": previews,
}
# All identical -- safe to replace just the first
idx = matches[0][0]
limit = self._char_limit(target)
# Check that replacement doesn't blow the budget
test_entries = entries.copy()
test_entries[idx] = new_content
new_total = len(ENTRY_DELIMITER.join(test_entries))
if new_total > limit:
return {
"success": False,
"error": (
f"Replacement would put memory at {new_total:,}/{limit:,} chars. "
f"Shorten the new content or remove other entries first."
),
}
entries[idx] = new_content
self._set_entries(target, entries)
self.save_to_disk(target)
return self._success_response(target, "Entry replaced.")
def remove(self, target: str, old_text: str) -> Dict[str, Any]:
"""Remove the entry containing old_text substring."""
old_text = old_text.strip()
if not old_text:
return {"success": False, "error": "old_text cannot be empty."}
with self._file_lock(self._path_for(target)):
bak = self._reload_target(target)
if bak:
return _drift_error(self._path_for(target), bak)
entries = self._entries_for(target)
matches = [(i, e) for i, e in enumerate(entries) if old_text in e]
if not matches:
return {"success": False, "error": f"No entry matched '{old_text}'."}
if len(matches) > 1:
# If all matches are identical (exact duplicates), remove the first one
unique_texts = {e for _, e in matches}
if len(unique_texts) > 1:
previews = [e[:80] + ("..." if len(e) > 80 else "") for _, e in matches]
return {
"success": False,
"error": f"Multiple entries matched '{old_text}'. Be more specific.",
"matches": previews,
}
# All identical -- safe to remove just the first
idx = matches[0][0]
entries.pop(idx)
self._set_entries(target, entries)
self.save_to_disk(target)
return self._success_response(target, "Entry removed.")
def format_for_system_prompt(self, target: str) -> Optional[str]:
"""
Return the frozen snapshot for system prompt injection.
This returns the state captured at load_from_disk() time, NOT the live
state. Mid-session writes do not affect this. This keeps the system
prompt stable across all turns, preserving the prefix cache.
Returns None if the snapshot is empty (no entries at load time).
"""
block = self._system_prompt_snapshot.get(target, "")
return block if block else None
# -- Internal helpers --
def _success_response(self, target: str, message: str = None) -> Dict[str, Any]:
entries = self._entries_for(target)
current = self._char_count(target)
limit = self._char_limit(target)
pct = min(100, int((current / limit) * 100)) if limit > 0 else 0
resp = {
"success": True,
"target": target,
"entries": entries,
"usage": f"{pct}% — {current:,}/{limit:,} chars",
"entry_count": len(entries),
}
if message:
resp["message"] = message
return resp
def _render_block(self, target: str, entries: List[str]) -> str:
"""Render a system prompt block with header and usage indicator."""
if not entries:
return ""
limit = self._char_limit(target)
content = ENTRY_DELIMITER.join(entries)
current = len(content)
pct = min(100, int((current / limit) * 100)) if limit > 0 else 0
if target == "user":
header = f"USER PROFILE (who the user is) [{pct}% — {current:,}/{limit:,} chars]"
else:
header = f"MEMORY (your personal notes) [{pct}% — {current:,}/{limit:,} chars]"
separator = "" * 46
return f"{separator}\n{header}\n{separator}\n{content}"
@staticmethod
def _read_file(path: Path) -> List[str]:
"""Read a memory file and split into entries.
No file locking needed: _write_file uses atomic rename, so readers
always see either the previous complete file or the new complete file.
"""
if not path.exists():
return []
try:
raw = path.read_text(encoding="utf-8")
except (OSError, IOError):
return []
if not raw.strip():
return []
# Use ENTRY_DELIMITER for consistency with _write_file. Splitting by "§"
# alone would incorrectly split entries that contain "§" in their content.
entries = [e.strip() for e in raw.split(ENTRY_DELIMITER)]
return [e for e in entries if e]
def _detect_external_drift(self, target: str) -> Optional[str]:
"""Return a backup-path string if on-disk content shows external drift.
The memory file is supposed to be a list of small entries the tool
wrote, joined by §. Detect drift via two signals:
1. Round-trip mismatch — re-parsing and re-serializing the file
doesn't produce identical bytes (rare; would catch oddly-encoded
delimiters).
2. Entry-size overflow — any single parsed entry exceeds the
store's whole-file char limit. The tool budgets the ENTIRE store
against that limit; no single tool-written entry can exceed it.
When we see one entry larger than the limit, an external writer
(patch tool, shell append, manual edit, sister session) appended
free-form content into what the tool will treat as one entry.
Flushing would then truncate that entry to the model's new
content, discarding the appended bytes — issue #26045.
Returns the absolute path of the .bak file when drift was found and
backed up; returns None when the file looks tool-shaped.
Note: this is an INSTANCE method (not static) because we need the
per-target char_limit for signal #2.
"""
path = self._path_for(target)
if not path.exists():
return None
try:
raw = path.read_text(encoding="utf-8")
except (OSError, IOError):
return None
if not raw.strip():
return None
parsed = [e.strip() for e in raw.split(ENTRY_DELIMITER) if e.strip()]
roundtrip = ENTRY_DELIMITER.join(parsed)
char_limit = self._char_limit(target)
max_entry_len = max((len(e) for e in parsed), default=0)
drift_detected = (raw.strip() != roundtrip) or (max_entry_len > char_limit)
if not drift_detected:
return None
# Drift confirmed — snapshot the file so the operator can recover
# whatever the external writer added, then return the .bak path so
# the caller can refuse the mutation.
ts = int(time.time())
bak_path = path.with_suffix(path.suffix + f".bak.{ts}")
try:
bak_path.write_text(raw, encoding="utf-8")
except (OSError, IOError):
return str(bak_path) + " (BACKUP FAILED — file unchanged on disk)"
return str(bak_path)
@staticmethod
def _write_file(path: Path, entries: List[str]):
"""Write entries to a memory file using atomic temp-file + rename.
Previous implementation used open("w") + flock, but "w" truncates the
file *before* the lock is acquired, creating a race window where
concurrent readers see an empty file. Atomic rename avoids this:
readers always see either the old complete file or the new one.
"""
content = ENTRY_DELIMITER.join(entries) if entries else ""
try:
# Write to temp file in same directory (same filesystem for atomic rename)
fd, tmp_path = tempfile.mkstemp(
dir=str(path.parent), suffix=".tmp", prefix=".mem_"
)
try:
with os.fdopen(fd, "w", encoding="utf-8") as f:
f.write(content)
f.flush()
os.fsync(f.fileno())
atomic_replace(tmp_path, path)
except BaseException:
# Clean up temp file on any failure
try:
os.unlink(tmp_path)
except OSError:
pass
raise
except (OSError, IOError) as e:
raise RuntimeError(f"Failed to write memory file {path}: {e}")
def memory_tool(
action: str,
target: str = "memory",
content: str = None,
old_text: str = None,
store: Optional[MemoryStore] = None,
) -> str:
"""
Single entry point for the memory tool. Dispatches to MemoryStore methods.
Returns JSON string with results.
"""
if store is None:
return tool_error("Memory is not available. It may be disabled in config or this environment.", success=False)
if target not in {"memory", "user"}:
return tool_error(f"Invalid target '{target}'. Use 'memory' or 'user'.", success=False)
if action == "add":
if not content:
return tool_error("Content is required for 'add' action.", success=False)
result = store.add(target, content)
elif action == "replace":
if not old_text:
return tool_error("old_text is required for 'replace' action.", success=False)
if not content:
return tool_error("content is required for 'replace' action.", success=False)
result = store.replace(target, old_text, content)
elif action == "remove":
if not old_text:
return tool_error("old_text is required for 'remove' action.", success=False)
result = store.remove(target, old_text)
else:
return tool_error(f"Unknown action '{action}'. Use: add, replace, remove", success=False)
return json.dumps(result, ensure_ascii=False)
def check_memory_requirements() -> bool:
"""Memory tool has no external requirements -- always available."""
return True
# =============================================================================
# OpenAI Function-Calling Schema
# =============================================================================
MEMORY_SCHEMA = {
"name": "memory",
"description": (
"Save durable information to persistent memory that survives across sessions. "
"Memory is injected into future turns, so keep it compact and focused on facts "
"that will still matter later.\n\n"
"WHEN TO SAVE (do this proactively, don't wait to be asked):\n"
"- User corrects you or says 'remember this' / 'don't do that again'\n"
"- User shares a preference, habit, or personal detail (name, role, timezone, coding style)\n"
"- You discover something about the environment (OS, installed tools, project structure)\n"
"- You learn a convention, API quirk, or workflow specific to this user's setup\n"
"- You identify a stable fact that will be useful again in future sessions\n\n"
"PRIORITY: User preferences and corrections > environment facts > procedural knowledge. "
"The most valuable memory prevents the user from having to repeat themselves.\n\n"
"Do NOT save task progress, session outcomes, completed-work logs, or temporary TODO "
"state to memory; use session_search to recall those from past transcripts.\n"
"If you've discovered a new way to do something, solved a problem that could be "
"necessary later, save it as a skill with the skill tool.\n\n"
"TWO TARGETS:\n"
"- 'user': who the user is -- name, role, preferences, communication style, pet peeves\n"
"- 'memory': your notes -- environment facts, project conventions, tool quirks, lessons learned\n\n"
"ACTIONS: add (new entry), replace (update existing -- old_text identifies it), "
"remove (delete -- old_text identifies it).\n\n"
"SKIP: trivial/obvious info, things easily re-discovered, raw data dumps, and temporary task state."
),
"parameters": {
"type": "object",
"properties": {
"action": {
"type": "string",
"enum": ["add", "replace", "remove"],
"description": "The action to perform."
},
"target": {
"type": "string",
"enum": ["memory", "user"],
"description": "Which memory store: 'memory' for personal notes, 'user' for user profile."
},
"content": {
"type": "string",
"description": "The entry content. Required for 'add' and 'replace'."
},
"old_text": {
"type": "string",
"description": "Short unique substring identifying the entry to replace or remove."
},
},
"required": ["action", "target"],
},
}
# --- Registry ---
from tools.registry import registry, tool_error
registry.register(
name="memory",
toolset="memory",
schema=MEMORY_SCHEMA,
handler=lambda args, **kw: memory_tool(
action=args.get("action", ""),
target=args.get("target", "memory"),
content=args.get("content"),
old_text=args.get("old_text"),
store=kw.get("store")),
check_fn=check_memory_requirements,
emoji="🧠",
)