Context compression plugin for OpenClaw. Compresses tool outputs, code, logs, and structured data — 70-90% token savings with zero LLM calls.

Recommended one-command setup:

headroom wrap openclaw

Manual install:

pip install "headroom-ai[proxy]"
openclaw plugins install --dangerously-force-unsafe-install headroom-ai/openclaw

This plugin can auto-start a local headroom proxy when needed. OpenClaw treats process-launching plugins as unsafe by default, so --dangerously-force-unsafe-install is required even if you plan to use a remote proxy (the capability is declared at install time).

If you are testing from this repo, run npm install/build from the plugin directory so local launcher detection aligns with runtime paths. These linked installs are supported:

cd plugins/openclaw
npm install
npm run build
openclaw plugins install --dangerously-force-unsafe-install --link .
openclaw plugins install --dangerously-force-unsafe-install --link dist

From the repo root, install the plugin directory explicitly:

openclaw plugins install --dangerously-force-unsafe-install --link ./plugins/openclaw

Or, from inside dist/:

cd plugins/openclaw/dist
openclaw plugins install --dangerously-force-unsafe-install --link .

Why this matters:

• The plugin checks launchers in this order: PATH -> local npm bin -> global npm -> python.
• "local npm bin" means plugins/openclaw/node_modules/.bin/headroom relative to the source checkout.
• Using --link dist (or --link . from dist/) still keeps runtime code adjacent to the checkout, and launcher detection falls back to PATH/global/python if a local npm bin is not present under the installed root.
• plugins/openclaw also carries a no-op hook shim so OpenClaw's hook-pack fallback treats the path as valid instead of emitting a misleading package.json missing openclaw.hooks warning.
• If you install from a .tgz, local npm bin may not exist in the installed extension and detection will fall back to PATH/global/python.

Install automatically selects the contextEngine slot for headroom on current OpenClaw releases. If you need to switch back manually, set plugins.slots.contextEngine to "legacy" or another engine id.

{
  "plugins": {
    "entries": {
      "headroom": {
        "enabled": true,
        "config": {
          "proxyUrl": "http://127.0.0.1:8787"
        }
      }
    },
    "slots": {
      "contextEngine": "headroom"
    }
  }
}

proxyUrl is optional. If omitted, the plugin auto-detects on localhost:

• http://127.0.0.1:<proxyPort>
• http://localhost:<proxyPort>

Default proxyPort is 8787.

By default, the plugin also rewrites the built-in openai-codex provider base URL to the active Headroom proxy at runtime. That means Codex provider traffic flows through Headroom, so /stats can observe real upstream request and cache activity instead of only local context compression.

This does not replace Headroom's existing Codex routing rules. The proxy already decides between api.openai.com and chatgpt.com/backend-api/codex/responses based on ChatGPT auth. The plugin change only points OpenClaw's provider config at the active proxy in memory and preserves the rest of the provider config.

You can also route additional provider ids such as anthropic, github-copilot, google, or openrouter through the same proxy:

{
  "plugins": {
    "entries": {
      "headroom": {
        "enabled": true,
        "config": {
          "gatewayProviderIds": ["openai-codex", "anthropic", "github-copilot", "google", "openrouter"]
        }
      }
    }
  }
}

When gatewayProviderIds is set, it becomes the exact list the plugin rewrites in memory for the current gateway process.

For convenience, the plugin also accepts family aliases:

• codex -> openai-codex
• claude -> anthropic
• copilot -> github-copilot
• gemini -> google

When OpenClaw has already resolved a provider's upstream baseUrl, the plugin preserves protocol-specific path segments while swapping only the origin. That keeps provider families on the right proxy route:

• Codex / ChatGPT backend: /backend-api
• OpenAI-compatible providers: /v1 or /api/v1
• GitHub Copilot Claude-family models: /anthropic
• Gemini: /v1beta

GitHub Copilot is a special case because OpenClaw can route it through either OpenAI Responses or Anthropic Messages depending on the selected model. The plugin only rewrites Copilot when OpenClaw has already resolved the upstream baseUrl, so it can preserve the correct /v1 or /anthropic path instead of guessing.

The routing is intentionally lightweight and reversible:

• the plugin does not persist provider baseUrl changes back to openclaw.json
• disabling the plugin, clearing gatewayProviderIds, or restarting without Headroom restores OpenClaw's normal provider resolution
• if you want durable provider rewrites, use headroom wrap openclaw instead of relying on plugin install side effects

If you need to disable that behavior:

{
  "plugins": {
    "entries": {
      "headroom": {
        "enabled": true,
        "config": {
          "routeCodexViaProxy": false
        }
      }
    }
  }
}

When proxyUrl points to localhost (or is omitted), the plugin will auto-start headroom proxy if no running proxy is detected. Launch order:

1. headroom from PATH
2. local npm bin (node_modules/.bin/headroom)
3. global npm bin
4. Python module (python -m headroom.cli proxy ...)

If pythonPath is set, it is tried first in the Python fallback step.

Docker-native Headroom installs intentionally leave pythonPath unset so this launcher order prefers the installed host headroom wrapper on PATH, which then runs Headroom in Docker.

Point proxyUrl to any reachable Headroom instance:

{
  "config": {
    "proxyUrl": "https://headroom.example.com:8787"
  }
}

Remote URLs are connect-only — the plugin probes the URL at startup and fails fast if the proxy is not reachable. No subprocess is spawned for remote addresses.

If you prefer to manage the proxy yourself (or are running a remote instance), start it before launching OpenClaw:

Python install:

pip install "headroom-ai[proxy]"
headroom proxy --host 127.0.0.1 --port 8787

NPM install:

npm install -g headroom-ai
headroom proxy --host 127.0.0.1 --port 8787

Every time OpenClaw assembles context for the model, the plugin compresses tool outputs and large messages:

• JSON arrays (tool outputs, search results) — statistical selection keeps anomalies, errors, boundaries
• Code — AST-aware compression via tree-sitter
• Logs — pattern deduplication, keeps errors and boundaries
• Text — ML-based token compression

Compression is lossless via CCR (Compress-Cache-Retrieve): originals are stored and the agent gets a headroom_retrieve tool to access full details when needed.

Apache-2.0