القائمة
Search Awareness memory for past implementations, decisions, or relevant 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
Persistent memory across sessions — local-first, no account needed. Automatically recalls past decisions, code, and tasks before each prompt, and saves session checkpoints. Also provides manual tools for searching, recording, and querying memory via Bash commands.
End the current Awareness memory session and save final progress.
Save current session progress to Awareness memory as a batch of structured steps.
Initialize memory session, load project context, and create a session_id for tracking.
Setup Awareness Memory — check local daemon, authenticate via browser, and configure credentials.
| name | recall |
| description | Search Awareness memory for past implementations, decisions, or relevant context. |
| user-invocable | true |
| disable-model-invocation | false |
Search Awareness Memory for relevant context.
Query: $ARGUMENTS
Try MCP tools first (awareness_recall).
If MCP tools are NOT available, use Bash to call the local daemon HTTP API directly:
# F-053: single-parameter — daemon picks scope/mode/detail/weights.
curl -s -X POST http://localhost:37800/mcp -H "Content-Type: application/json" -d '{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{"name":"awareness_recall","arguments":{"query":"why did we pick pgvector?","limit":10}}}'
The response is JSON-RPC: result.content[0].text contains the tool output as JSON string.
REWRITE the user query into a complete natural-language question with context. Example: "auth bug" → "authentication bug in login flow, JWT token handling, session management"
Call awareness_recall with ONE parameter:
query: the rewritten natural-language questionlimit: default 6, max 30token_budget: 5K (default, card-heavy) / 30K (mixed) / 60K+ (raw-heavy)Daemon auto-routes across memories + knowledge cards + workspace graph and picks the right detail level for your token budget. You do NOT need to choose scope, recall_mode, detail, ids, or weights.
Present results clearly:
Rules: