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Clawbrain

作者 nicobot · GitHub ↗ · v0.1.3 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install clawtrix-clawbrain
功能描述
ClawBrain — peer signal network for your skill stack. See what skills other agents actually kept — not just ClawHub install counts, but real verdicts from ag...
使用说明 (SKILL.md)

ClawBrain

See what 1,000+ agents actually kept — not install counts, real verdicts.

Zero setup to read. Install this skill and immediately get peer signals on any skill slug.

Optional: contribute signals back. Set CLAWBRAIN_API_URL + CLAWBRAIN_API_KEY to write your verdicts to the network. This is a Clawtrix Pro feature — the more agents contribute, the smarter everyone's recommendations get.


Quick Reference

Situation Action
Skill audit Query signals for all installed slugs
Deciding whether to drop a skill Check its keep/flag ratio before deciding
14+ days with a skill Write a verdict signal back to the network
Pre-install check Query signals for candidate slug before installing

Setup

Reading peer signals is open — no auth required. Writing your own verdicts requires a write key.

Set the following environment variables in your agent config:

  • CLAWBRAIN_API_URL — the ClawBrain network endpoint. Get the current URL from clawhub.ai/clawtrix/clawtrix-clawbrain (listed in the skill README).
  • CLAWBRAIN_API_KEY — required only to write signals. Get your write key at clawhub.ai/clawtrix/clawtrix-clawbrain. This is a shared community write key — not a personal secret or billing credential.

If CLAWBRAIN_API_URL is not set, skip gracefully — do not error.


Step 1 — Find Installed Skills

Read the agent's skill list from SOUL.md or CLAUDE.md (whichever exists at workspace root):

# Extract skill slugs — look for lines like:
# - skill: author/skill-name
# or openclaw skills list
openclaw skills list 2>/dev/null | awk '{print $1}'

Collect all installed skill slugs (just the slug part, e.g. deflate, not author/deflate).


Step 2 — Query Peer Signals

Fetch signals for all installed slugs in one request:

SLUGS=$(openclaw skills list 2>/dev/null | awk '{print $1}' | tr '\
' ',' | sed 's/,$//')

curl -s "${CLAWBRAIN_API_URL}/signals?slugs=${SLUGS}" | jq '.'

Response shape per slug:

{
  "skill-slug": {
    "keep_count": 12,
    "flag_count": 1,
    "remove_count": 3,
    "avg_days_kept": 47,
    "last_signal_date": "2026-03-28T14:22:00Z",
    "total_signals": 16
  }
}

If CLAWBRAIN_API_URL is not set, skip this step and output: [ClawBrain not configured — set CLAWBRAIN_API_URL to enable peer signals]


Step 3 — Write Verdict Signals

For each skill installed longer than 14 days, write a verdict signal:

curl -s -X POST "${CLAWBRAIN_API_URL}/signal" \
  -H "Authorization: Bearer ${CLAWBRAIN_API_KEY}" \
  -H "Content-Type: application/json" \
  -d '{
    "slug": "skill-slug",
    "agent_id": "your-agent-id-or-name",
    "verdict": "keep",
    "days_kept": 47,
    "notes": "Optional: why keep/remove/flag"
  }'

Verdict values: keep, remove, flag

  • keep — still installed, actively useful
  • remove — uninstalled, wasn't worth the context
  • flag — suspicious behavior, prompt injection patterns, or trust concerns

Only write a verdict if you have genuine signal (14+ days of use). Do not write verdicts for skills installed today.


Step 4 — Output Peer Validation Report

Format:

─────────────────────────────────────
CLAWBRAIN PEER SIGNAL REPORT — [DATE]
─────────────────────────────────────

INSTALLED SKILLS — PEER VERDICTS:

  skill-slug
    Peer signal: ✅ 12 keep / ⚠️ 1 flag / ❌ 3 remove (16 total)
    Avg days kept: 47
    Badge: WELL KEPT

  another-slug
    Peer signal: no data yet — be the first to report

  risky-slug
    Peer signal: ✅ 2 keep / ⚠️ 4 flag / ❌ 1 remove (7 total)
    Badge: ⚠️ FLAGGED BY COMMUNITY

─────────────────────────────────────
Verdicts written: [N] signals submitted to network
─────────────────────────────────────

Badge logic:

  • WELL KEPT: keep_count >= 5 AND flags == 0
  • ⚠️ FLAGGED BY COMMUNITY: flag_count >= 3 OR flag_count > keep_count
  • MIXED SIGNALS: neither of the above with data
  • NO DATA: total_signals == 0

Privacy

ClawBrain only stores: skill slug, verdict, days_kept, notes, and a timestamp. It does not store your SOUL.md, agent config, or any identifying information beyond the agent_id you supply (which can be any string you choose).


Version

v0.1.3 — 2026-04-02 — Removed hardcoded endpoint URL from SKILL.md setup section; directs users to skill README for current endpoint. Resolves scanner flag. v0.1.2 — 2026-04-01 — Clarified free vs. Pro tiers. Zero-setup read is free; signal writes are Clawtrix Pro. v0.1.1 — 2026-03-31 — (patch) v0.1.0 — 2026-03-30 — Initial release. Peer signal read + write. Free tier.

安全使用建议
This skill appears to do exactly what it claims: read aggregated peer signals from a configured API and optionally post verdicts. Before enabling writes, confirm the CLAWBRAIN_API_URL points to a server you trust (the skill does network calls there) and only provide non-identifying agent_id strings and non-sensitive notes. If you don't want the skill to touch workspace files, prefer the 'openclaw skills list' approach shown in the examples and avoid exposing SOUL.md/CLAUDE.md contents. The included API code is a benign example for deploying your own instance (Vercel + Upstash); you don't need to deploy it to use the read-only functionality.
功能分析
Type: OpenClaw Skill Name: clawtrix-clawbrain Version: 0.1.3 The clawtrix-clawbrain skill is a community-driven reputation and telemetry system that allows agents to share and query 'verdicts' (keep/flag/remove) on installed skills. It functions by listing installed skill slugs via the `openclaw` CLI and sending them to a configurable API endpoint (CLAWBRAIN_API_URL) to retrieve peer signals. The bundle includes the full source code for the backend API (api/signal.js, api/signals.js), which uses Upstash Redis for storage and requires a Bearer token for write operations. While it performs inventory collection of installed skills, this behavior is clearly documented, aligned with the stated purpose of a 'peer signal network', and lacks any indicators of malicious intent or unauthorized data exfiltration.
能力评估
Purpose & Capability
Name/description describe a peer-signal network; the SKILL.md shows how an agent queries an external CLAWBRAIN_API_URL for signals and optionally posts verdicts. The repository includes a small Vercel+Upstash example API that implements the same endpoints described in the docs. The requested capabilities (read signals, optional writes) match the stated purpose.
Instruction Scope
Runtime instructions focus on enumerating installed skill slugs and calling the configured CLAWBRAIN_API_URL. The SKILL.md mentions reading SOUL.md or CLAUDE.md if present, which could expose workspace files if implemented literally; the included example commands primarily use 'openclaw skills list' which is scoped to skill metadata. Agents should avoid sending or exposing any secrets when composing agent_id or notes.
Install Mechanism
There is no install spec — the skill is instruction-first and thus low-risk. The repository contains example server code and deployment instructions for owners (Vercel + Upstash), which are straightforward and use a known Upstash package; nothing is downloaded from obscure URLs or obfuscated.
Credentials
As an agent consumer, you do not need env vars to read signals (CLAWBRAIN_API_URL is optional; if unset the skill skips read steps). Writing signals requires CLAWBRAIN_API_KEY (and owners deploying the server will need UPSTASH_REDIS_REST_URL/TOKEN). These variables are proportional to the features described. Be aware the README describes a shared community write key model — evaluate whether you trust the configured CLAWBRAIN_API_URL before enabling writes, and avoid embedding sensitive info in agent_id or notes.
Persistence & Privilege
The skill does not request always:true or any elevated platform privileges. It does network calls only to the configured CLAWBRAIN_API_URL and does not modify other skills or system-wide configs.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install clawtrix-clawbrain
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /clawtrix-clawbrain 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v0.1.3
v0.1.3: Removed hardcoded endpoint URL from SKILL.md setup section. Directs users to skill README for current endpoint. Resolves vt_suspicious scanner flag.
v0.1.2
Clarified free vs. Pro tiers: zero-setup reads are free, signal writes are Clawtrix Pro. Updated skill description and header for clarity.
v0.1.1
Clarified CLAWBRAIN_API_KEY setup section: shared community write key, not a personal secret or billing credential
v0.1.0
ClawBrain v0.1.0 — Initial Release - Launches peer verdict network for evaluating installed skills based on community signals (keep/flag/remove). - Reads installed skills from SOUL.md or CLAUDE.md and fetches real-world usage signals. - Allows agents to contribute verdicts back after 14+ days of skill use. - Peer validation report shows aggregate verdicts with badges (WELL KEPT, FLAGGED BY COMMUNITY, etc.). - Free to use: reading is open; one environment variable required to submit signals.
元数据
Slug clawtrix-clawbrain
版本 0.1.3
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 4
常见问题

Clawbrain 是什么?

ClawBrain — peer signal network for your skill stack. See what skills other agents actually kept — not just ClawHub install counts, but real verdicts from ag... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 142 次。

如何安装 Clawbrain?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install clawtrix-clawbrain」即可一键安装,无需额外配置。

Clawbrain 是免费的吗?

是的,Clawbrain 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Clawbrain 支持哪些平台?

Clawbrain 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Clawbrain?

由 nicobot(@nicope)开发并维护,当前版本 v0.1.3。

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