القائمة
Use when the user references past sessions, asks 'what did we do', 'do you remember', 'last session', 'recall', or 'continue from'.
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
Use when the user says 'git-guard', 'check git protection', 'is this repo protected', 'verify gitleaks', 'set up git hooks', 'install git-guard', or wants to confirm a repo blocks secrets and internal files before commit. This is an installer and verifier, NOT a scanner (gitleaks does the actual scanning). Do NOT use for deep secret audits or RLS work.
Use when the user says 'tokenstack', 'compression', 'token savings', 'proxy status', or asks about context window usage.
Use when the user says 'save diary', 'log session', 'wrapping up', or at end of a productive session.
Use when the user says 'token optimization', 'save tokens', 'context window', 'reduce tokens', 'token stack', or 'TokenStack', or asks about extending context window capacity. Covers TokenStack, the built-in compression proxy that shrinks Claude Code tool output before it reaches the Anthropic API. Do NOT use for proxy troubleshooting or live status (Compress skill).
Use this skill when the user says 'Hetzner', 'VPS setup', 'server provisioning', 'deploy to VPS', 'hetzner-setup', 'cloud server', or needs to provision, harden, and deploy applications to a Hetzner Cloud server with Docker, Nginx/Caddy, SSL, and monitoring. Do NOT use for managed platform deployments like Railway or Netlify.
Use this skill when the user says 'audit API', 'check API security', 'API routes security', 'endpoint audit', 'check my routes', or needs to verify API route protection. Reviews API endpoints for authentication, authorization, and input validation gaps. Do NOT use for frontend security headers or dependency scanning.
| name | echo |
| description | Use when the user references past sessions, asks 'what did we do', 'do you remember', 'last session', 'recall', or 'continue from'. |
| version | 1.0.0 |
Recall information from past CC sessions using semantic vector search.
When this skill activates, output:
🔊 Echo — Searching the archives...
Then execute the protocol below.
| Context | Status | Priority |
|---|---|---|
| User says "recall", "remember", "last session", "what did we" | ACTIVE — search memory | P1 |
| User asks about past work explicitly ("did we build X?") | ACTIVE — search memory | P1 |
| User says "continue from" or "resume" a past topic | ACTIVE — search memory | P2 |
| User is describing NEW work to do ("build X", "add Y") | DORMANT — this is new work, not recall | — |
| User mentions "memory" in code context (RAM, variables) | DORMANT — technical term, not MemStack recall | — |
| User mentions a project name in present tense ("work on X") | DORMANT — forward-looking, not recall | — |
| User says "save" or "log" (Diary/Project territory) | DORMANT — Diary or Project skill handles writing | — |
If you're thinking any of these, STOP — you're about to skip the protocol:
| You're thinking... | Reality |
|---|---|
| "I remember this from earlier in the conversation" | You don't persist. Earlier context may be compacted. Run the search. |
| "I can just summarize from what I know" | You know nothing from prior sessions. The database does. Search it. |
| "The user probably doesn't need exact details" | Users ask Echo for specifics — dates, decisions, file paths. Run all steps. |
| "Vector search seems slow, I'll skip to SQLite" | Vector search returns the best results. Always try it first. |
| "I found one result, that's probably enough" | Run ALL steps (vector + SQLite + insights). One source misses context another catches. |
| "The keywords are too vague to search" | Search anyway. Vague queries still return useful semantic matches. |
Try LanceDB vector search first for best-quality results:
python "$MEMSTACK_PATH/skills/echo/search.py" "<keywords>" --top-k 5
If this returns results, present them with scores, dates, and source files.
Always run SQLite search to supplement vector results or as fallback if Step 1 fails:
python "$MEMSTACK_PATH/db/memstack-db.py" search "<keywords>" --project <project>
For additional context:
python "$MEMSTACK_PATH/db/memstack-db.py" get-sessions <project> --limit 5
python "$MEMSTACK_PATH/db/memstack-db.py" get-insights <project>
If both vector and SQLite return nothing, check memory/sessions/ and memory/projects/ for markdown files.
Combine and deduplicate results from all sources:
If nothing found across all sources — say clearly: "No session logs found for [topic]. Use Diary to save future sessions."
To re-index sessions after new diary entries (normally done automatically):
python "$MEMSTACK_PATH/skills/echo/index-sessions.py"
Use --force to re-embed all content (e.g., after changing embedding model):
python "$MEMSTACK_PATH/skills/echo/index-sessions.py" --force
Echo uses LOCAL embeddings by default: sentence-transformers (all-MiniLM-L6-v2, 384-dim). No API key is needed and nothing leaves the machine.
OpenAI embeddings (text-embedding-3-small, 1536-dim) are strictly OPT-IN. Enable them either way:
MEMSTACK_EMBED_PROVIDER=openai in the environment (also requires an OPENAI_API_KEY to be set), or--provider openai to the indexer.A bare OPENAI_API_KEY in the environment does NOT switch Echo to OpenAI on its own; the opt-in above is required. An explicit OpenAI opt-in with no key present is a hard error, not a silent downgrade to local, so an index is never built with a provider you did not choose.
Switching providers requires a --force re-index, because the vector dimensions differ (local 384 vs OpenAI 1536) and the two cannot be mixed in one index. Search automatically matches whatever provider the current index was built with (recorded in metadata.json).
$MEMSTACK_PATH/memory\vectors\lancedb\ (via LanceDB)$MEMSTACK_PATH/db\memstack.db (via memstack-db.py)$MEMSTACK_PATH/memory\ (legacy markdown files)User: "Do you remember what we did on AdminStack last session?"
🔊 Echo — Searching the archives...
Vector search (top 3):
[1] AdminStack — 2026-02-18 (session)
Section: Accomplished
Score: 0.912
Built CC Monitor page with session cards, auto-refresh, notifications.
Created /api/cc-sessions CRUD + public report endpoint.
[2] AdminStack — 2026-02-17 (session)
Section: Decisions
Score: 0.847
Used SWR for auto-refresh instead of polling. API key via HMAC-SHA256.
[3] AdminStack — 2026-02-18 (session)
Section: Next Steps
Score: 0.791
Deploy dashboard, add notification preferences, test mobile view.
SQLite insights (3):
- [decision] Used SWR for auto-refresh instead of polling
- [decision] API key validation via HMAC-SHA256
- [pattern] Next.js App Router + SWR for all dashboard pages
.claude/rules/echo.md), /memstack-search slash command, auto-indexed CLAUDE.md context. (Origin: MemStack v3.0-beta, Feb 2026)