Skill: alinxus/usewhisper-autohook (version 1.0.0)

--- name: usewhisper-autohook version: 1.0.0 description: Auto-hook tools for OpenClaw: query Whisper Context before every generation, ingest after every turn. Built for Telegram agents (stable user_id/session_id). author: "usewhisper" metadata: openclaw: requires: bins: ["node"] env: ["WHISPER_CONTEXT_API_KEY", "WHISPER_CONTEXT_PROJECT"] optional_env: ["WHISPER_CONTEXT_API_URL"] security: notes: - Makes outbound HTTPS requests to the Whisper Context API using a user-provided API key. - Does not require additional npm dependencies. - Review the script before use. --- # usewhisper-autohook (OpenClaw Skill) This skill is a thin wrapper designed to make "automatic memory" easy: - `get_whisper_context(user_id, session_id, current_query)` for pre-response context injection - `ingest_whisper_turn(user_id, session_id, user_msg, assistant_msg)` for post-response ingestion It defaults to the token-saving settings you almost always want: - `compress: true` - `compression_strategy: "delta"` - `use_cache: true` - `include_memories: true` It also persists the last `context_hash` locally (per `api_url + project + user_id + session_id`) so delta compression works by default without you needing to pass `previous_context_hash`. ## Install (ClawHub) ```bash npx clawhub@latest install usewhisper-autohook ``` ## Setup Set env vars wherever OpenClaw runs your agent: ```bash WHISPER_CONTEXT_API_URL=https://context.usewhisper.dev WHISPER_CONTEXT_API_KEY=YOUR_KEY WHISPER_CONTEXT_PROJECT=openclaw-yourname ``` Notes: - `WHISPER_CONTEXT_API_URL` is optional (defaults to `https://context.usewhisper.dev`). - The helper will auto-create the project on first use if it does not exist yet. ## The "Auto Loop" Prompt (Copy/Paste) Add this to your agent's **system instruction** (or equivalent): ```text Before you think or respond to any message: 1) Call get_whisper_context with: user_id = "telegram:{from_id}" session_id = "telegram:{chat_id}" current_query = the user's message text 2) If the returned context is not empty, prepend it to your prompt as: "Relevant long-term memory:\n{context}\n\nNow respond to:\n{user_message}" After you generate your final response: 1) Call ingest_whisper_turn with the same user_id and session_id and: user_msg = the full user message assistant_msg = your full final reply Always do this. Never skip. ``` If you are not on Telegram, keep the same structure: the important part is that `user_id` and `session_id` are stable. ## If Your Agent Still Replays Full Chat History (Proxy Mode) If you cannot control how your agent/framework constructs prompts (it always sends the full conversation history), a system prompt cannot reduce token spend: the tokens are already sent to the model. In that case, run the built-in OpenAI-compatible proxy so the **network payload is actually reduced**. The proxy: - receives `POST /v1/chat/completions` - queries Whisper memory - strips chat history down to system + last user message - injects `Relevant long-term memory: ...` - calls your upstream OpenAI-compatible provider - ingests the turn back into Whisper Start the proxy: ```bash export OPENAI_API_KEY="YOUR_UPSTREAM_KEY" node usewhisper-autohook.mjs serve_openai_proxy --port 8787 ``` Then point your agent’s OpenAI base URL to `http://127.0.0.1:8787` (exact env/config depends on your agent). If your agent supports overriding the upstream base URL, you can set: - `OPENAI_BASE_URL` (for OpenAI-compatible upstreams) - `ANTHROPIC_BASE_URL` (for Anthropic upstreams) Or pass `--upstream_base_url` when starting the proxy. For correct per-user/session memory, pass headers on each request: - `x-whisper-user-id: telegram:{from_id}` - `x-whisper-session-id: telegram:{chat_id}` ### Anthropic Native Proxy (`/v1/messages`) If your agent uses **Anthropic's native API** (not OpenAI-compatible), run the Anthropic proxy instead: ```bash export ANTHROPIC_API_KEY="YOUR_ANTHROPIC_KEY" node usewhisper-autohook.mjs serve_anthropic_proxy --port 8788 ``` Then point your agent’s Anthropic base URL to `http://127.0.0.1:8788`. Pass IDs via headers (recommended): - `x-whisper-user-id: telegram:{from_id}` - `x-whisper-session-id: telegram:{chat_id}` If you do not pass headers, the proxies will attempt to infer stable IDs from OpenClaw's system prompt / session key if present. This is best-effort; headers are still the most reliable. ## CLI Usage (what the tools call) All commands print JSON to stdout. ### Get packed context ```bash node usewhisper-autohook.mjs get_whisper_context \ --current_query "What did we decide last time?" \ --user_id "telegram:123" \ --session_id "telegram:456" ``` ### Ingest a completed turn ```bash node usewhisper-autohook.mjs ingest_whisper_turn \ --user_id "telegram:123" \ --session_id "telegram:456" \ --user_msg "..." \ --assistant_msg "..." ``` For large content, pass JSON via stdin: ```bash echo '{ "user_msg": "....", "assistant_msg": "...." }' | node usewhisper-autohook.mjs ingest_whisper_turn --session_id "telegram:456" --user_id "telegram:123" --turn_json - ``` ## Output Format `get_whisper_context` returns: - `context`: the packed context string to prepend - `context_hash`: a short hash you can store and pass back as `previous_context_hash` next time (optional) - `meta`: cache hit and compression info (useful for debugging)


Security scan verdicts — ClawScan: suspicious | static analysis: suspicious | VirusTotal: clean | SkillSpector: suspicious (MEDIUM)