Skill: alinxus/usewhisper (version 1.0.0)

--- name: whisper-context version: 0.1.0 description: Official Whisper Context skill for OpenClaw. Cuts context tokens via delta compression + caching, and adds long-term memory across sessions. author: "Whisper" 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. --- # Whisper Context (OpenClaw Skill) Reduce OpenClaw API spend by shrinking the context you send to the model (delta compression + caching), while keeping long-term memory across sessions. This skill provides a minimal Node-based helper (`whisper-context.mjs`) that OpenClaw agents can run to: - Retrieve packed context for a user/session (`query_context`) with `compress: true` and `compression_strategy: "delta"` - Persist the latest turn into long-term memory (`ingest_session`) - Write/search memories (`memory_write`, `memory_search`) - Run Oracle search/research (`oracle_search`) - Fetch cost analytics (`get_cost_summary`) - Inspect/warm cache (`cache_stats`, `cache_warm`) ## Install (ClawHub) ```bash npx clawhub@latest install whisper-context ``` ClawHub installs the skill folder into your OpenClaw skills workspace (typically `~/.openclaw/workspace/skills/`). ## Setup Set environment variables (where OpenClaw reads env for your agent): ```bash WHISPER_CONTEXT_API_URL=https://context.usewhisper.dev WHISPER_CONTEXT_API_KEY=YOUR_KEY WHISPER_CONTEXT_PROJECT=openclaw-cost-optimization ``` Notes: - `WHISPER_CONTEXT_API_URL` is optional (defaults to `https://context.usewhisper.dev`). - `WHISPER_CONTEXT_PROJECT` can be a project slug/name. - If the project does not exist yet, the helper will auto-create it in your org on first use. - For best memory behavior, use stable `user_id` and `session_id` values (don’t hardcode them globally; derive them per user/session in your agent). ## Usage All commands print JSON to stdout. ### Global flags - `--project <slugOrName>`: override `WHISPER_CONTEXT_PROJECT` - `--api_url <url>`: override `WHISPER_CONTEXT_API_URL` - `--timeout_ms <n>`: request timeout (default: 30000) ### Tips for real agents (to actually slash spend) - Always call `query_context` first and inject the returned `context` instead of re-sending your entire chat history. - Keep `compress: true`, `compression_strategy: "delta"`, and `use_cache: true` (the defaults in this helper) to maximize token savings. - Use stable `user_id` and `session_id` so memory works across sessions and cache keys stay effective. ### Query packed context ```bash node whisper-context.mjs query_context \ --query "What did we decide about the retriever cache?" \ --user_id "user-123" \ --session_id "session-123" ``` ### Ingest a completed turn ```bash node whisper-context.mjs ingest_session \ --user_id "user-123" \ --session_id "session-123" \ --user "..." \ --assistant "..." ``` If your message text is large or hard to shell-escape, pass JSON via stdin: ```bash echo '{ "user": "....", "assistant": "...." }' | node whisper-context.mjs ingest_session --session_id "session-123" --turn_json - ``` ## Security / Privacy Notes - `ingest_session` sends both user and assistant text to the Context API (so it can build memory and improve retrieval). - The helper only reads local files if you explicitly pass `@path` (or stdin via `-`). - Treat your `WHISPER_CONTEXT_API_KEY` like a secret; don’t commit it to git. ### Write a memory ```bash node whisper-context.mjs memory_write \ --memory_type "preference" \ --content "User prefers concise answers." \ --user_id "user-123" ``` ### Search memories ```bash node whisper-context.mjs memory_search \ --query "preferences" \ --user_id "user-123" ``` ### Oracle search / research ```bash node whisper-context.mjs oracle_search --query "How does delta compression work?" --mode search node whisper-context.mjs oracle_search --query "Design a plan..." --mode research --max_steps 3 ``` ### Cost summary ```bash node whisper-context.mjs get_cost_summary \ --start_date "2026-01-01T00:00:00.000Z" \ --end_date "2026-02-01T00:00:00.000Z" ``` ### Cache stats (prove your savings) ```bash node whisper-context.mjs cache_stats ``` ### Cache warm (optional) ```bash node whisper-context.mjs cache_warm --queries "retriever cache,l1 query cache,delta compression" --ttl_seconds 3600 ``` ## Agent Integration Pattern 1. Before calling the model: run `query_context` and prepend the returned `context` (if present) to your prompt. 2. After replying: run `ingest_session` with the user + assistant messages to persist memory. ## Troubleshooting - `Missing WHISPER_CONTEXT_API_KEY`: export the env var where OpenClaw runs commands. - `HTTP 401/403`: verify your API key and that it has access to the project/org. - `HTTP 404 Project not found`: verify `WHISPER_CONTEXT_PROJECT` (slug/name) exists.


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