القائمة
Retrieve coding patterns from GLOBAL vector database (cross-project learning). Auto-invokes when TodoWrite has >3 tasks or when user says "--recall". Searches relevant role collections based on task context.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
| name | memory-recall |
| description | Retrieve coding patterns from GLOBAL vector database (cross-project learning). Auto-invokes when TodoWrite has >3 tasks or when user says "--recall". Searches relevant role collections based on task context. |
The memory-only agent has ZERO access to Read/Write/Edit/Glob/Bash - it can ONLY use MCP memory tools. This prevents file reading pollution by design.
Search when: Non-obvious bugs, complex architectures, performance issues, unfamiliar domains, hard problems.Skip when: Obvious tasks, basic file operations, standard workflows, problems solvable with basic knowledge.
Hook Activation Condition:
Example: "Need to implement rate limiting for REST API to prevent abuse. Backend service in Node.js with Express. Want proven pattern that prevents thundering herd. Current setup uses Redis for session storage. Need to rate limit by IP address with 100 requests per minute. Must handle distributed deployments with multiple server instances. Looking for battle-tested implementation that won't add significant latency."
Step 2: Detect relevant roles Determine which role collections to search based on task context. Use role_mapping below. Default to ["OTHER"] if unclear. Can search multiple roles when task spans domains.
Step 3: Search previews
Use search_memory with query, roles=["detected_role", "OTHER"], limit=30.
Note: The roles parameter tells MCP which collections to search.
Step 4: Analyze previews Review returned previews (preview text ONLY). Select 3-5 most relevant based on:
Note: Score doesn't matter - don't trust similarity scores. Focus on analyzing the preview text content.
Step 5: Retrieve full content
Use batch_get_memories with selected doc_ids and roles=["detected_role", "OTHER"].
Note: batch_get_memories needs roles parameter to know which collections to search in.
Step 6: Present results Format retrieved memories clearly. Let the main agent decide what to apply.
<role_mapping> Available roles (maps to Qdrant collections):
Default to "OTHER" if unclear. Each role corresponds to a separate Qdrant collection.
Search multiple role collections when task spans domains (e.g., ["backend", "devops", "OTHER"] for API deployment task). </role_mapping>
