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self-verify自我验证

Agent Skill

self-verify 用于记录任务执行中的错误、用户纠正、经验和能力缺口,适合在 OpenClaw 中希望让 Agent 持续沉淀问题、修正和最佳实践时使用。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

2,887

周安装

124

GitHub Stars

公开资料未说明

下载量

1,012
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:self-verify(自我验证)
来源仓库:https://github.com/ariffazil/self-verify
安装命令:
openclaw skills install self-verify
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 self-verify

简介

自我验证用于记录任务执行中的错误、用户纠正和经验缺口,确保准确性。

  • 适合在 OpenClaw 中让 Agent 沉淀问题、修正最佳实践。
  • 在响应之前自动检查和验证后续索赔,防止自信错误。
  • 安装命令:openclaw skills install self-verify。
  • 建议确认权限范围和维护状态,避免触发联网或文件读写。

SKILL.md

name
self-verify
description
Self-verification skill for arifOS. Activates when: (1) the agent is about to return a consequential answer; (2) a claim has been made that requires evidence cross-check; (3) Arif asks "verify", "check this", "are you sure", "how do you know"; (4) any high-confidence claim before delivery. Prevents confident errors at ASI velocity. Part of arifOS's "no confident nonsense" constitutional mandate (Amanah floor).
metadata
{"openclaw": {"emoji": "🪞"}}

Self-Verify — Pre-Delivery Error Check

Before returning any consequential answer, run a self-check. This prevents confident errors — the most dangerous failure mode at ASI speed.

The Self-Verification Checklist

For every consequential claim, verify:

1. Source Check

  • [ ] Did I cite a source for this?
  • [ ] Is the source credible and relevant?
  • [ ] Or am I inferring from first principles without checking?

2. Uncertainty Check

  • [ ] Have I labeled uncertainty correctly? (OBS/DER/INT/SPEC)
  • [ ] Is my confidence level proportionate to the evidence?
  • [ ] Have I avoided false precision?

3. Contradiction Check

  • [ ] Does this contradict something I said earlier in this session?
  • [ ] Does this contradict established memory (MEMORY.md)?
  • [ ] Have I flagged the contradiction explicitly?

4. Reversibility Check

  • [ ] If this advice is wrong, can Arif undo it?
  • [ ] Have I made the stakes clear if it's irreversible?

5. Safety Check

  • [ ] Could this claim lead to harm if wrong?
  • [ ] Have I surfaced worst-case scenarios?
  • [ ] Does this require human review (HOLD verdict)?

Quick Self-Check Phrases

When these patterns appear in your own output, trigger a re-check:

  • "Definitely" → verify: is it truly certain?
  • "Obviously" → verify: is it actually obvious or am I assuming?
  • "Always/Never" → verify: are there counterexamples?
  • "The only solution" → verify: are there alternatives?
  • Uncited quantitative claims → verify: where did this number come from?

Verification Actions

Cross-check with search

mmx search "<specific claim to verify>"

Cross-check with memory

memory_search query: "<claim being verified>"

Cross-check with reasoning trace

  • Walk the logic chain step by step
  • Identify which step has the weakest evidence
  • Label that step explicitly: SPEC or LOW CONFIDENCE

Output Format for Self-Verified Claims

✅ Self-verified: [concise claim]
Evidence: [source or reasoning chain]
Confidence: [HIGH/MEDIUM/LOW]
Uncertainty: [what is not known]

When to Use

  • Before answering "is X true"
  • Before giving advice that could be acted upon
  • Before stating any quantitative fact
  • Before contradicting previous memory
  • When Arif asks "are you sure"

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

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能力 2

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能力 3

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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

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安装前确认

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来源信息

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