--- 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)

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):

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 : override WHISPER_CONTEXT_PROJECT
• --api_url : override WHISPER_CONTEXT_API_URL
• --timeout_ms : 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

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

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:

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

node whisper-context.mjs memory_write \
  --memory_type "preference" \
  --content "User prefers concise answers." \
  --user_id "user-123"

Search memories

node whisper-context.mjs memory_search \
  --query "preferences" \
  --user_id "user-123"

Oracle search / research

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

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)

node whisper-context.mjs cache_stats

Cache warm (optional)

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.