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Agent Skill · 研究检索

proof-of-work(工作证明)

proof-of-work 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 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。

proof-of-work 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为接触敏感数据;许可证为 MIT,第三方扫描有未通过项,按安装量在研究检索类的 73,675 个 Skill 里排第 46,340。

总安装 784周安装 33GitHub Stars 264下载 275核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT

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:proof-of-work(工作证明)
来源仓库:https://github.com/athola/claude-night-market
仓库路径:skills/proof-of-work
安装命令:
npx skills add https://github.com/athola/claude-night-market --skill proof-of-work
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。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/athola/claude-night-market --skill proof-of-work

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

用于查找和检索工作量证明机制、区块链共识或密码学相关资料。适合在分布式系统设计或加密算法研究中提供支持。使用时需结合具体协议版本和安全假设进行分析。proof-of-work 属于研究检索类 Skill,可作为该场景下的辅助能力补充。建议验证来源仓库是否包含最新攻击案例和防御进展。

涉及实际部署时应评估算力成本和能源消耗影响。

来源仓库内路径:skills/proof-of-work

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/athola/claude-night-market --skill proof-of-wo…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

proof-of-work 怎么安装?

在终端执行 npx skills add https://github.com/athola/claude-night-market --skill proof-of-work。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

proof-of-work 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

proof-of-work 需要什么权限?

权限级别是接触敏感数据。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。

proof-of-work 是免费的吗?

来源标注的许可证是 MIT。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

proof-of-work 用的人多吗?

公开数据是累计安装 784 次,近一周安装 33 次,下载 275 次,GitHub 264 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

proof-of-work 安全吗?

第三方扫描有未通过项,风险较高。除非你确认过源码,否则不建议直接安装到常用环境。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 3 个目录同时收录,说明这个 Skill 流传比较广。
  • 许可证明确为 MIT,商用和分发边界好判断。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
proof-of-work

工作证明 · 本页

784264接触敏感数据MIT未通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Claims without evidence fail the people who depend on your work. Proof-of-work is humility in practice: "it looks correct" is not "I verified it works."

Proof of Work

Table of Contents

Overview

The "Proof of Work" methodology prevents premature completion claims by requiring technical verification before stating that a task is finished. For example, instead of assuming an LSP configuration functions after a restart, we verify that the server starts and that tools respond to queries. This approach confirms the solution works before the user attempts validation.

Before claiming completion, provide reproducible evidence of the solution's performance and address edge cases. All claims must be backed by actual command output captured in the current environment.

The Iron Law

NO IMPLEMENTATION WITHOUT A FAILING TEST FIRST NO COMPLETION CLAIM WITHOUT EVIDENCE FIRST NO CODE WITHOUT UNDERSTANDING FIRST

The Iron Law prevents testing from becoming a perfunctory exercise. If an implementation is planned before tests are written, the RED phase fails to drive the design. Understand the technical rationale for an approach and its limitations before declaring it done. Before writing code, document evidence of the failure being addressed and confirm that tests are driving the implementation.

Verification and TDD Workflow

Verify the fundamentals of the implementation and the reasons for choosing it over alternatives. Identify where a solution might fail rather than stating it should always work. The TDD cycle follows these mandatory steps:

  1. RED: Write a failing test before implementation.
  2. GREEN: Create a minimal implementation that passes the test.
  3. REFACTOR: Improve the code without changing its behavior.

Iron Law Self-Check

Self-Check QuestionIf Answer Is WrongAction
Do I have documented evidence of failure/need?NoSTOP - document failure first
Am I testing pre-conceived implementation?YesSTOP - let test DRIVE design
Am I feeling design uncertainty?NoSTOP - uncertainty is GOOD
Did test drive implementation?NoSTOP - doing it backwards

Iron Law Progress Tracking

  • proof:iron-law-red: Failing test written before implementation.
  • proof:iron-law-green: Minimal implementation passes test.
  • proof:iron-law-refactor: Code improved without behavior change.
  • proof:iron-law-coverage: Coverage gates passed (line, branch, and mutation).

Confirm that work passes all line, branch, and mutation coverage gates. For detailed enforcement patterns, see iron-law-enforcement.md.

Usage Standards

Apply this skill before stating that work is "done," "finished," or "ready." Use it before recommending solutions or stating that a configuration "should work." Stop if you find yourself assuming a configuration is correct without testing it or recommending a fix without first reproducing the problem. Red flags include thinking "this looks correct" without actual verification. If you cannot explain each line of a configuration or why a specific practice applies to the current context, the necessary validation steps have been skipped.

Validation Protocol

Step 1: Reproduce the Problem (proof:problem-reproduced)

Before proposing a solution, verify the current state. Use tools like ps, echo, and cat to check running processes, environment variables, and configuration files. Document the failure with command output and error logs.

Step 2: Test the Solution (proof:solution-tested)

Before claiming a solution works, execute it in the current environment. Capture the actual output and confirm that it matches expected behavior. Do not rely on assumed output.

Step 3: Check for Known Issues (proof:edge-cases-checked)

Research known bugs and limitations related to the approach. Check GitHub issues, version compatibility, and official documentation to identify potential blockers or common pitfalls.

Step 4: Capture Evidence (proof:evidence-captured)

Use imbue:proof-of-work to document the commands executed, their output, timestamps, and the conclusions drawn from each step.

Step 5: Prove Completion (proof:completion-proven)

Define acceptance criteria and validate each item. If a blocker is identified, document the diagnosis with evidence and provide workaround options instead of claiming completion.

Integration

With Improvement Workflows

Use proof-of-work to validate improvement opportunities identified by /update-plugins or /fix-workflow. Document the baseline metrics (step count, failure rate, duration), test the proposed changes, and capture the improved metrics to demonstrate quantitative impact.

Validation Checklist (Before Claiming "Done")

Verify that the problem was reproduced with evidence and the solution was tested in the actual environment. Research known issues and consider edge cases. Capture evidence in a reproducible format and confirm that all acceptance criteria are met. The completion statement must detail the specific tests run and their results, citing evidence for each claim.

Red Flag Self-Check

Before sending a completion message, confirm that you have run the recommended commands and captured their output. Verify that you have researched known issues and that the validation steps are reproducible by the user. Ensure you are proving rather than assuming.

Supporting Modules

Exit Criteria

Complete all progress tracking items. Create an evidence log with reproducible proofs. Define and validate acceptance criteria, and document any identified blockers.

平台分布

Claude Code

29.6%
按下载量换算81

OpenCode

24.63%
按下载量换算68

Cursor

18.34%
按下载量换算50

Codex

13.07%
按下载量换算36

Antigravity

7.95%
按下载量换算22

Gemini CLI

3.54%
按下载量换算10

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

未通过

权限和风险

接触敏感数据

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。

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