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clawdocclawdoc 搜索

Agent Skill

clawdoc 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

5,832

周安装

243

GitHub Stars

公开资料未说明

下载量

1,944
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:clawdoc(clawdoc 搜索)
来源仓库:https://github.com/ashishjaingithub/clawdoc
安装命令:
openclaw skills install clawdoc
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install clawdoc

简介

clawdoc 使用 14 个模式检测器诊断代理故障与成本问题。

  • 适合任务失败、成本异常或性能下降时使用。
  • 支持快速定位问题与优化行为路径。clawdoc 属于研究检索类 Skill,可作为该场景下的辅助能力补充。
  • 安装命令:openclaw skills install clawdoc,建议确认日志访问权限。
  • 使用前请核实是否会触发日志读取或外部分析调用。

SKILL.md

name
clawdoc
version
0.12.0
description
Diagnose OpenClaw agent failures, cost spikes, and performance issues with 14 pattern detectors. Use when: task failed unexpectedly, costs seem high, agent burned tokens, debugging session problems, want a health check, reviewing agent performance, agent forgot context, agent kept retrying, agent said commands but didn't execute them, cron jobs getting expensive, heartbeat costs too high, agent drifted off task after compaction, agent stuck reading without editing, agent running find/grep on entire filesystem, agent re-reading same file repeatedly.
user-invocable
true
metadata
openclaw
emoji
🩻
requires
bins

clawdoc

Examine agent sessions. Diagnose failures. Prescribe fixes.

Invocation modes

/clawdoc (slash command — default: headline mode)

Produces a compact, tweetable health check:

🩻 clawdoc — 3 findings across 12 sessions (last 7 days)
💸 $47.20 spent — $31.60 was waste (67% recoverable)
🔴 Retry loop on exec burned $18.40 in one session
🟡 Opus running 34 heartbeats ($8.20 → $0.12 on Haiku)
🟡 SOUL.md is 9,200 tokens — 14% of your context window

Run: bash {baseDir}/scripts/headline.sh ~/.openclaw/agents/main/sessions

/clawdoc full or "give me a full diagnosis"

Runs all 14 pattern detectors and produces the complete diagnosis report with evidence and prescriptions.

/clawdoc brief or "clawdoc one-liner for daily brief"

Single-line summary for morning cron integration:

Yesterday: 8 sessions, $3.40, 1 warning (cron context growth on daily-report)

Run: bash {baseDir}/scripts/headline.sh --brief ~/.openclaw/agents/main/sessions

Natural language triggers

Also activates when user says: "what went wrong", "why did that fail", "debug", "diagnose", "why was that so expensive", "where are my tokens going", "cost breakdown", "health check", "check my agent", "what's wrong", "examine"

Quick examination — most recent session

Find the most recent session file and run:

bash {baseDir}/scripts/examine.sh <session.jsonl>

This outputs a JSON summary with turns, cost, token counts, tool call frequency, and error count.

Single-session diagnosis

Run all 14 pattern detectors against a specific session file:

bash {baseDir}/scripts/diagnose.sh <session.jsonl> | jq .

Diagnosis with prescriptions

Pipe diagnose output into prescribe for a formatted report with fix recommendations:

bash {baseDir}/scripts/diagnose.sh <session.jsonl> | bash {baseDir}/scripts/prescribe.sh

Cost breakdown

Show per-turn cost waterfall for a session:

bash {baseDir}/scripts/cost-waterfall.sh <session.jsonl> | jq '.[0:5]'

Cross-session pattern recurrence

Analyze pattern recurrence across multiple sessions in a directory:

bash {baseDir}/scripts/history.sh <sessions-dir> | jq .

Full diagnosis

When the user wants a comprehensive diagnosis, run the scripts above and synthesize findings into this report format:

Diagnosis report format

## 🩻 Diagnosis — [date]

### Patient summary
- Sessions examined: N
- Period: [date range]
- Total spend: $X.XX
- Total tokens: XXk in / XXk out

### Findings

#### 🔴 Critical
[Infinite retry loops, context exhaustion, tool-as-text failures]
Each finding includes: what happened, evidence, estimated cost impact, and specific prescription.

#### 🟡 Warning
[Cost spikes, model routing waste, cron accumulation, compaction damage, workspace overhead]

#### 🟢 Healthy
[What's working well — efficient sessions, good model routing]

### Prescriptions (ranked by cost impact)
1. [Highest-impact fix with specific config change or command]
2. [Second highest]
3. [Third]

### Cost breakdown
[Per-day costs for the examination period]
[Top 3 most expensive sessions with root cause]

Pattern reference

#PatternSeverityKey indicator
1Infinite retry loop🔴 CriticalSame tool called 5+ times consecutively
2Non-retryable error retried🔴 HighValidation error → identical retry
3Tool calls as text🔴 HighTool names in assistant text, no toolCall blocks
4Context window exhaustion🟡-🔴inputTokens > 70% of contextTokens
5Sub-agent replay🟡 MediumDuplicate completion messages in parent
6Cost spike🟡-🔴Session cost > 2x rolling average
7Skill selection miss🟢 Low"command not found" after skill activation
8Model routing waste🟡 MediumPremium model on heartbeat/cron
9Cron context accumulation🟡 MediumGrowing inputTokens across cron runs
10Compaction damage🟡 MediumPost-compaction tool call repetition
11Workspace token overhead🟡 MediumBaseline > 15% of context window
12Task drift🟡 MediumPost-compaction directory divergence or 10+ reads without edits
13Unbounded walk🟠 HighRepeated unscoped find/grep -r flooding output
14Tool misuse🟡 MediumSame file read 3+ times without edit, or identical search repeated

Self-improving-agent integration

To enable writing findings to .learnings/LEARNINGS.md, set CLAWDOC_LEARNINGS=1 before running prescribe:

CLAWDOC_LEARNINGS=1 bash {baseDir}/scripts/diagnose.sh <session.jsonl> | bash {baseDir}/scripts/prescribe.sh

Tips

  • Session JSONL files are the ground truth for all diagnostics
  • Use jq -s (slurp) for aggregations across all lines in a session file
  • Filter message.content[] by type=="text" for readable content, type=="toolCall" for tool invocations
  • When prescribing config changes, always show the exact JSON path and value

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

76.63%
按下载量换算1,490

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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