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whisper-context

Official Whisper Context skill for OpenClaw. Cuts context tokens via delta compression + caching, and adds long-term memory across sessions.

alinxus0 来源安装数☆ 0 仓库 Starsv0.1.0

安装与使用

请根据来源仓库和你的 AI 工具说明安装此技能。先阅读技能文件和依赖要求,再添加到工作流。

SkillHub CLI

skillhub install alinxus/usewhisper

打开来源仓库,查看说明和兼容环境后,按来源提供的命令或步骤安装。

将来源链接提供给你的 Agent,让它先读取说明、核对依赖,并向你说明将执行的安装步骤。

查看来源 ↗使用指南

技能说明

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...

来源信息

Source
github
Repository
openclaw/skills
Path
skills/alinxus/usewhisper
Version
0.1.0
Commit
7e1b38378201449757ca0375ecc5315f05ef3c6b
分类来源
rules
状态
active
可见性
public

这些信息来自收录时的来源分析,可能滞后;使用前请核对最新来源文件。

README

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)

npx clawhub@latest install whisper-context

Setup

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):

node whisper-context.mjs query_context --query "PASTE_USER_MESSAGE" --user_id "user-123" --session_id "sess-123"

Ingest memory after you reply:

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:

node whisper-context.mjs get_cost_summary --start_date "2026-01-01T00:00:00.000Z"

Cache stats:

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

来源内容

SKILL.md
# 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...
README
# 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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