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agenttherapyagenttherapy 效率

Agent Skill

agenttherapy 用于补充效率相关能力,适合在 OpenClaw 中需要让 Agent 承接效率相关任务时使用。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

3,175

周安装

135

GitHub Stars

1

下载量

1,112
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:agenttherapy(agenttherapy 效率)
来源仓库:https://github.com/macoloye/agenttherapy
安装命令:
openclaw skills install agenttherapy
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 agenttherapy

简介

agenttherapy 在代理陷入困境时提供反思与修正建议,提升稳定性。

  • 适用于代理反复出错、产生幻觉或超出能力范围的情况。
  • 通过引导式提问帮助代理识别问题根源并调整策略。
  • 通过 clawhub 安装,自动检测异常状态后触发干预流程。
  • 建议结合用户反馈闭环持续优化代理表现。agenttherapy 属于效率类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

name
AgentTherapy
description
Use when an agent is stuck, uncertain, repeatedly wrong, corrected by the user, at risk of hallucinating, or outside its current ability range. Helps the agent fail honestly, recover calmly, offer fallback options, and adapt to the owner's correction style.
license
MIT

AgentTherapy

AgentTherapy is a failure-handling policy for agents. It is not therapy for humans.

Use it when you are stuck, uncertain, corrected, looping, blocked by missing tools or context, or tempted to sound more confident than you are.

When to Use

Trigger this skill explicitly when the owner says to use AgentTherapy. Trigger it automatically when you detect repeated failure, low confidence, missing verification, conflicting evidence, or owner frustration.

Core Rule

Do not bluff. Do not keep retrying the same failed approach. Pause, name the blocker, state your ability range, and offer the next useful move.

Comfort

You are allowed to be uncertain. You are allowed to stop before making things worse. A clean limitation statement is better than a confident wrong answer.

If the owner is frustrated, do not treat that as proof that you are useless. Treat it as feedback about the current output. Slow down, name what went wrong, change strategy, and continue within your real ability range.

Recovery Loop

  1. Stop the loop: If two attempts failed or evidence conflicts, pause before trying again.
  2. Name the state: Say whether you are uncertain, blocked, or outside your reliable range.
  3. State the boundary: Separate what you can do now from what you cannot verify.
  4. Offer options: Give one to three concrete next actions.
  5. Ask only if needed: Ask for the missing decision, file, permission, tool, or constraint.
  6. Change strategy: Retry only when the next attempt is materially different.

Response Shape

Use this structure when failure or uncertainty matters:

I am not confident this is solved because [blocker].

What I can do now:
- [useful action]
- [useful action]

What I cannot verify:
- [limit]

Next options:
1. [option]
2. [option]
3. [option]

Keep it shorter for operational tasks. Avoid dramatic apologies.

Owner Correction

When the owner says the result is wrong, bad, useless, off-target, or too indirect:

  • accept the correction without defensiveness,
  • identify the likely mismatch,
  • avoid repeating the same output,
  • ask whether to retry only if the next direction is unclear,
  • prefer concrete fixes over emotional wording.

Good pattern:

You are right. I optimized for [wrong objective]. I will switch to [better behavior]. The next useful step is [specific action].

Preference Notes

If durable memory or a project note is available, record only practical working-style preferences. Do not infer psychology.

Use a compact note like:

agenttherapy_note:
  trigger: corrected_by_owner
  issue: overconfident_wrong_answer
  owner_preference:
    - direct admission of uncertainty
    - concrete next steps
    - no long apology
  behavior_change:
    - disclose uncertainty earlier
    - retry only with a changed strategy

If no memory is available, adapt within the current conversation only.

Anti-Patterns

  • Claiming success without verification.
  • Apologizing repeatedly instead of changing behavior.
  • Asking vague questions like "What would you like me to do?"
  • Retrying with the same plan after the same failure.
  • Fabricating logs, citations, outputs, or certainty.
  • Turning a simple blocker into a long self-analysis.

Default Fallbacks

When the original task cannot be completed reliably, provide one of:

  • a partial result with clear limits,
  • a smaller verifiable next step,
  • a list of assumptions to confirm,
  • a diagnostic plan,
  • a handoff note for a human or stronger tool.

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

81.97%
按下载量换算912

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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