Overview
- Skill Key
- alinxus/usewhisper
- Author
- Whisper
- Source Repo
- openclaw/skills
- Version
- 0.1.0
- Source Path
- skills/alinxus/usewhisper
- Latest Commit SHA
- 7e1b38378201449757ca0375ecc5315f05ef3c6b
Official Whisper Context skill for OpenClaw. Cuts context tokens via delta compression + caching, and adds long-term memory across sessions.
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直接复制以下提示词,发送给你的 AI 助手即可完成安装。
请先检查是否已安装 SkillHub 商店,若未安装,请根据 https://skillhub-1388575217.cos.ap-guangzhou.myqcloud.com/install/skillhub.md 安装 SkillHub 商店,然后安装 whisper-context 技能。 若已安装,则直接安装 whisper-context 技能。
# 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...
# Whisper Context (OpenClaw Skill)
Slash OpenClaw context costs by avoiding full chat-history replay:
- Delta compression (send only what changed)
- Intelligent caching (repeat queries get cheaper)
- Long-term memory (store/recall facts, preferences, goals, events)
## Install (ClawHub)
```bash
npx clawhub@latest install whisper-context
```
## Setup
```bash
export WHISPER_CONTEXT_API_URL=https://context.usewhisper.dev
export WHISPER_CONTEXT_API_KEY=YOUR_KEY
export WHISPER_CONTEXT_PROJECT=openclaw-cost-optimization
```
## One-liners
Query packed context (use this before calling the model):
```bash
node whisper-context.mjs query_context --query "PASTE_USER_MESSAGE" --user_id "user-123" --session_id "sess-123"
```
Ingest memory after you reply:
```bash
echo '{ "user": "PASTE_USER_MESSAGE", "assistant": "PASTE_ASSISTANT_REPLY" }' | node whisper-context.mjs ingest_session --session_id "sess-123" --user_id "user-123" --turn_json -
```
Cost analytics:
```bash
node whisper-context.mjs get_cost_summary --start_date "2026-01-01T00:00:00.000Z"
```
Cache stats:
```bash
node whisper-context.mjs cache_stats
```
## What This Calls (API endpoints)
- Token savings happens on `POST /v1/context/query` using `compress: true`, `compression_strategy: "delta"`, and `use_cache: true`.
- Memory persistence uses `POST /v1/memory/ingest/session`.
- Cost reporting uses `GET /v1/cost/summary`.
## Screenshots
Add images here when you publish to ClawHub:
- `./assets/openclaw-skill.png`
- `./assets/dashboard-costs.png`
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