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 <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

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.