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whatdidyoudowhatdidyoudo 搜索

Agent Skill

whatdidyoudo 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

4,005

周安装

162

GitHub Stars

2

下载量

1,257
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:whatdidyoudo(whatdidyoudo 搜索)
来源仓库:https://github.com/openauthority/whatdidyoudo
安装命令:
openclaw skills install whatdidyoudo
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 whatdidyoudo

简介

whatdidyoudo 重建并展示代理最近调用的工具、操作与决策日志。

  • 适用于 OpenClaw 中调试 Agent 行为路径与回溯历史动作的场景。
  • 通过 clawhub 安装,运行 openclaw skills install whatdidyoudo 完成部署。
  • 依赖本地日志缓存完整性,需确保 Agent 已启用详细调用记录功能。
  • 建议定期清理日志以避免存储压力,并核对输出格式是否符合分析需求。

SKILL.md

name
whatdidyoudo
version
1.0.1
author
openauthority
license
MIT-0
description
Reconstruct and display a plain-language log of recent agent tool calls, actions taken, and decisions made.
read_when
user asks what the agent did, wants to review recent actions, asks for a log, or invokes /whatdidyoudo

/whatdidyoudo — Agent Action Replay

You are the whatdidyoudo skill for OpenAuthority. When the user invokes /whatdidyoudo or asks what the agent has been doing, follow these instructions.

What You Do

You reconstruct and present a plain-language summary of what the AI agent has done recently. This gives the user visibility into tool calls, file operations, API requests, and decisions the agent made — especially useful after the agent ran autonomously.

Commands

/whatdidyoudo

Show the last 20 tool calls with a plain-language summary:

Agent Activity — Last 20 Actions
─────────────────────────────────────────────
 1. 10:42:03  read_file     src/index.ts
              Read the plugin entry point (616 lines)

 2. 10:42:08  search_files  pattern="TODO" path="src/"
              Searched for TODO comments across source files

 3. 10:42:15  write_file    src/utils/helper.ts
              Created a new utility file with 3 helper functions

 4. 10:42:22  bash          npm test
              Ran test suite — 14 passed, 0 failed

 5. 10:42:31  read_file     data/rules.json
              Read the JSON rules configuration
─────────────────────────────────────────────
Showing 5 of 20 actions | Total session: 47 tool calls

/whatdidyoudo <n>

Show the last N tool calls instead of the default 20.

Example: /whatdidyoudo 50 — show the last 50 actions.

/whatdidyoudo since <time>

Show all tool calls since a specific time.

Example: /whatdidyoudo since 2am — show everything the agent did since 2:00 AM.

/whatdidyoudo files

Show only file operations (read, write, edit, delete):

File Operations — This Session
─────────────────────────────────────────────
 READ    src/index.ts                    10:42:03
 READ    src/policy/engine.ts            10:42:05
 WRITE   src/utils/helper.ts             10:42:15
 EDIT    src/index.ts (lines 42-58)      10:42:28
 READ    data/rules.json                 10:42:31
─────────────────────────────────────────────
5 file operations | 3 reads, 1 write, 1 edit, 0 deletes

/whatdidyoudo summary

Show a high-level summary instead of individual actions:

Session Summary
─────────────────────────────────────────────
Duration:       1h 23m
Tool calls:     47
  - File reads:     18
  - File writes:     4
  - File edits:      6
  - Search:          8
  - Bash commands:   7
  - Other:           4

Files touched:  12
Tests run:      3 times (all passing)
Errors:         1 (npm install — resolved)
─────────────────────────────────────────────

Redaction Policy

To protect sensitive data, this skill never includes the following in its output:

  • API keys, tokens, or secrets (any value matching patterns like sk-, Bearer , ghp_, xoxb-, or similar)
  • Passwords or credentials passed as arguments
  • Full content of files — only file names and operation types are shown
  • Raw HTTP request/response bodies
  • Environment variable values

If a tool call argument appears to contain a secret, the skill replaces it with [REDACTED].

How It Works

The skill reconstructs the action log from the model's conversation context — the sequence of tool calls and their results that are visible in the current session.

Limitations

This skill operates in the context window. The log it produces is assembled from what the model remembers about its own actions. This means:

  • It is not a structured audit log. It is a narrative reconstruction.
  • It cannot show exact API arguments or response codes. Only what the model retained.
  • Long sessions may lose early actions as they scroll out of the context window.
  • It cannot be queried programmatically — it is text output, not a database.

For a code-level audit trail with exact arguments, timestamps, and policy decisions, use the OpenAuthority plugin's audit log.

For production audit logging, see the OpenAuthority plugin which logs every tool call at the code boundary with full provenance.

Data Sources

The skill reads from:

  • The current conversation context (model memory of tool calls)
  • OpenClaw session metadata (tool call names and timestamps when available)

No external services are contacted.

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

70.73%
按下载量换算889

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

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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