usewhisper-autohook

name	usewhisper-autohook
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).

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)

npx clawhub@latest install usewhisper-autohook

Setup

Set env vars wherever OpenClaw runs your agent:

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):

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.