proof-of-work

proof-of-work is a skill for Claude Code, Codex from MadAppGang/claude-code. It costs 24 tokens per session (1,470 once invoked), scanned A, original, MIT.

A task-checking guide for producing evidence that completed coding work is correct, such as screenshots, test results, build output, or a deployment link.

In plain words
What is it for?
Use it to document completed tasks, verify interface changes with screenshots, report test outcomes, and assess confidence before accepting work.
Why use it?
It removes guesswork about how to prove that a bug fix or feature works. It also helps decide whether the available evidence is sufficient for approval.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to document completed tasks, verify interface changes with screenshots, report test outcomes, and assess confidence before accepting work.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/madappgang/claude-code/proof-of-work
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add MadAppGang/claude-code --skill proof-of-work
Clone the repo
git clone --depth 1 https://github.com/MadAppGang/claude-code

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for proof-of-work

README.md
[![agentmods](https://agentmods.dev/badge/skills/madappgang/claude-code/proof-of-work/github.svg)](https://agentmods.dev/skills/madappgang/claude-code/proof-of-work)
Your own site
<a href="https://agentmods.dev/skills/madappgang/claude-code/proof-of-work"><img src="https://agentmods.dev/badge/skills/madappgang/claude-code/proof-of-work/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for proof-of-work

Your own site · 80×15
<a href="https://agentmods.dev/skills/madappgang/claude-code/proof-of-work"><img src="https://agentmods.dev/badge/skills/madappgang/claude-code/proof-of-work.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 24 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,470 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00024 $0.01470
Opus 5 $0.00012 $0.00735
Sonnet 5 $0.00005 $0.00294
Haiku 4.5 $0.00002 $0.00147

Measured 9d ago against content hash eab6e200ef95, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

proof-of-work scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

plugins/autopilot/skills/proof-of-work/SKILL.md · 235 lines

How it starts

The opening of the file, as written. The whole thing — 235 lines — stays where its author put it; the contents beside it link to each section on GitHub.

plugin: autopilot updated: 2026-01-20

Proof-of-Work

Version: 0.1.0 Purpose: Generate validation artifacts for autonomous task completion Status: Phase 1

When to Use

Use this skill when you need to:

  • Generate proof artifacts after task completion
  • Capture screenshots for UI verification
  • Parse and report test results
  • Calculate confidence scores for task validation
  • Determine if a task can be auto-approved

Overview

Proof-of-work is the mechanism that validates task completion. Every finished task must include verifiable artifacts that demonstrate the work was done correctly.

Proof Types by Task

Bug Fix Proof

Artifact Required Purpose
Git diff Yes Show minimal, focused changes
Test results Yes All tests passing
Regression test Yes Specific test for the bug
Error log (before/after) Optional Visual evidence

Feature Proof

Artifact Required Purpose
Screenshots Yes Visual verification
Test results Yes Functionality works
Coverage report Yes >= 80% coverage
Build output Yes Builds successfully
Deployment URL Optional Live demo

UI Change Proof

Artifact Required Purpose
Desktop screenshot Yes 1920x1080 view
Mobile screenshot Yes 375x667 view
Tablet screenshot Yes 768x1024 view
Accessibility score Yes >= 80 Lighthouse
Visual regression Optional BackstopJS diff

Screenshot Capture

Playwright Pattern:

import { chromium } from 'playwright';

async function captureScreenshots(url: string, outputDir: string) {
  const browser = await chromium.launch({ headless: true });
  const context = await browser.newContext();
  const page = await context.newPage();

  // Desktop
  await page.setViewportSize({ width: 1920, height: 1080 });
  await page.goto(url);
  await page.waitForLoadState('networkidle');
  await page.screenshot({
    path: `${outputDir}/desktop.png`,
    fullPage: true,
  });

  // Mobile
  await page.setViewportSize({ width: 375, height: 667 });
  await page.goto(url);
  await page.waitForLoadState('networkidle');
  await page.screenshot({
    path: `${outputDir}/mobile.png`,
    fullPage: true,
  });

  // Tablet
  await page.setViewportSize({ width: 768, height: 1024 });
  await page.goto(url);
  await page.waitForLoadState('networkidle');
  await page.screenshot({
    path: `${outputDir}/tablet.png`,
    fullPage: true,
  });

  await browser.close();
}

Read the full file on GitHub · 235 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 9d ago First seen · 235 lines · 24 tokens per session scan A eab6e200ef95

Subscribe to this mod's changes

proof-of-work is a skill published in the GitHub repository MadAppGang/claude-code (279 stars, last pushed 5mo ago), licensed MIT. It adds 24 tokens to every session and 1,470 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Related

Other skills, from other repositories

debugging-failures

Diagnose a failing Ginkgo suite as an agent — always run with --json-report into a predictable temp/gitignored location, read the terminal verdict line, then use jq to extract structured failure details (name, message, file:line, panic value, captured logs). Covers the panicked-vs-failed trap, panic locations pointing…

onsi/ginkgo · 122 tokens

smiles-validation

Strict SMILES validation, structural comparison, and modification verification. Catches invalid LLM-generated molecules.

synthetic-sciences/openscience · 24 tokens

hypothesis-testing

Applies the scientific method to debugging by helping users form specific, testable hypotheses, design targeted experiments, and systematically confirm or reject theories to find root causes. Use when a user says their code isn't working, they're getting an error, something broke, they want to troubleshoot a bug, or…

rohitg00/skillkit · 103 tokens

doris-debug-deployment

Use for Doris FE/BE startup failures, port conflicts, prioritynetworks misrouting, metadir corruption, and ADD/DROP BACKEND issues.

apache/doris-skills · 36 tokens

app-platform-troubleshooting

Debug running App Platform applications by accessing containers, analyzing logs, running diagnostics, and applying fixes. Use when apps fail to deploy, crash at runtime, have connectivity issues, or need performance diagnosis.

digitalocean-labs/do-app-platform-skills · 45 tokens

k8s-troubleshoot

Debug Kubernetes pods, nodes, and workloads. Use when pods are failing, containers crash, nodes are unhealthy, or users mention debugging, troubleshooting, or diagnosing Kubernetes issues.

rohitg00/kubectl-mcp-server · 41 tokens