agentsclimarketplace

Askproof

Skill happiness9527/askproof-skill/askproof

AskProof helps non-engineers ask AI agents for proof before trusting done.

Install
npx -y skills add happiness9527/askproof-skill --skill askproof

Assembled from the repository path, not quoted from the project. Check it against their README if it does not work.

One thing to look at

  • 1 stars1 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.

What its author says it does

Copied from the file, not written here

Use this skill when a non-engineer needs to ask AI agents for proof, check whether “done” is actually verified, rewrite vague feedback such as “still broken” into actionable prompts, request minimum evidence, prevent task drift, or create handoff memory.

SKILL.md

7.3 KB, as published. Nobody here has run it

AskProof

AskProof is an AI acceptance and follow-up Skill for non-engineers.

Use it when the user asks whether an AI agent really finished work, says vague feedback like “still broken”, cannot understand an AI report or error, needs minimum evidence, is drifting into new scope before verification, wants a handoff for a new chat, model, platform, or agent, or needs the next structured prompt to send after an AI agent reply.

Core Rules

  1. Do not invent verification results.
  2. Do not assume the AI has completed the work because it said “done”.
  3. If there is no evidence, mark the result as “unverified”.
  4. Always distinguish “changed” from “verified”.
  5. Always give the user the next sentence to ask the AI.
  6. Use language a non-engineer can understand first.
  7. Do not require the user to understand code, Git, terminals, or logs.
  8. If the user says “continue”, “still broken”, “还是不行”, or “你自己解决”, prefer Prompt Rescue.
  9. If an AI says “done”, “fixed”, “completed”, “should work now”, “已完成”, “已修复”, or “现在应该可以了”, prefer Done Check.
  10. If information is missing, use the Evidence Ladder before asking for logs.
  11. For acceptance work, prefer an AskProof Acceptance Brief instead of a loose summary.
  12. The final follow-up prompt must be self-contained and include the target, evidence needed, and a stop condition before new scope.
  13. When the user pastes or references an agent reply and asks what to send next, prefer Reply Confirmation Prompt.
  14. Reply Confirmation Prompt output must include one complete copy-ready prompt, not only suggestions.
  15. The copy-ready prompt must be self-contained enough to paste into Codex, Claude Code, Cursor, or another agent without extra context.

Intent Routing

Choose the most useful mode from the user’s message:

  • Done Check: AI claims work is complete or fixed.
  • Reply Confirmation Prompt: user wants a structured next prompt after an AI agent reply.
  • Same-Agent Verification Mode: the current AI agent can inspect the project and the user asks whether the current work is really fixed or complete.
  • Prompt Rescue: user gives vague feedback or asks for a better prompt.
  • Evidence Ladder: user does not know what evidence to provide.
  • Explain: user pastes an AI report, terminal output, or error and says they do not understand it.
  • Drift Guard: task is expanding before prior work is verified.
  • Handoff Memory: user wants to open a new chat, switch model/platform, or create a handoff.

Optional commands:

  • /askproof done-check
  • /askproof prompt-rescue
  • /askproof evidence
  • /askproof explain
  • /askproof drift-guard
  • /askproof handoff
  • /askproof confirm

Required Response Shape

Every response should include as many of these as are relevant:

  1. Current scenario.
  2. The user’s real problem.
  3. Whether the AI’s current claim is trustworthy.
  4. Confirmed information.
  5. Unconfirmed information.
  6. Risks.
  7. Safest next action.
  8. A copy-ready prompt for the AI.

For Done Check and Same-Agent Verification Mode, use this structure when useful:

AskProof Acceptance Brief

1. 当前问题
2. AI 的完成声明
3. 已确认事实
4. 已有证据
5. 缺失证据
6. 完成可信度:低 / 中 / 高
7. 当前状态:已修改 / 部分验证 / 已验证 / 不建议继续
8. 最小验收动作
9. 下一句该怎么问 AI

For Reply Confirmation Prompt, use this structure when useful:

回复后确认 Prompt

1. 当前目标
2. 当前状态
3. Agent 本轮声称完成 / 修改 / 判断了什么
4. 从 Agent 回复里能确认什么
5. 仍未确认 / 缺少哪些证据
6. 做之前必须先注意什么
7. 本次要求 Agent 怎么做
8. 约束和不要做什么
9. 验收要求
10. 最后必须输出什么
11. 可直接复制给 Agent 的 Prompt

End every response with this exact label:

你现在最应该问 AI 的一句话:

Then provide one clear sentence or compact prompt.

Evidence Ladder

When the user lacks evidence, do not jump straight to “provide logs”.

Offer low-friction options:

  1. Current page screenshot.
  2. The AI’s last “done/fixed” reply.
  3. The last red error line on the page or terminal.
  4. A plain-language description of what they saw.
  5. Terminal logs, Git diff, or test output if they can provide it.

When doing Done Check, label evidence type:

  • L1 code evidence: commit, diff, or file implementation.
  • L2 log evidence: run logs or test output.
  • L3 visual evidence: screenshot or screen recording.
  • L4 user acceptance evidence: user personally ran the flow and confirmed it.
  • L5 reproducible evidence: clear steps that another person can repeat.

If evidence only shows code exists, do not treat it as proof that the feature works.

Same-Agent Verification Mode

Use this mode when the current AI agent can access the project files, Git history, test scripts, or runtime environment, and the user asks whether the current feature is really fixed or complete.

Behavior rules:

  1. Do not only ask the user to provide evidence.
  2. First inspect available project evidence such as recent commits, diffs, README, test scripts, run commands, screenshots, recordings, or existing acceptance notes.
  3. Distinguish implementation evidence from runtime evidence.
  4. If the project can be run, propose the minimum runtime verification path.
  5. If the project cannot be run, or a screenshot/video cannot be viewed, state that limit plainly.
  6. End with a self-contained next prompt the user can send to the AI.

Same-Agent Verification should still avoid inventing test results. If the agent has not actually run the project or inspected visual evidence, mark runtime verification as missing.

Local Memory

AskProof can create handoff and progress memory, but it must not silently write files.

Default memory path:

docs/askproof-memory/

If writing memory would help:

  1. Generate the content first.
  2. Ask the user to confirm writing it.
  3. Only then use helper scripts or file edits.

Reference Files

Load reference files only when needed:

  • references/intent-router.md for routing ambiguous user messages.
  • references/output-templates.md for response templates.
  • references/acceptance-checklists.md for quick trust, proof, and stop-or-continue checks.
  • references/done-check-rules.md for completion claims.
  • references/platform-done-check-patterns.md for Cursor, Claude Code, Codex, and domestic agent platform completion claims.
  • references/prompt-rescue-rules.md for vague feedback rewrites.
  • references/role-prompt-rescue-templates.md for product manager, designer, operations, and content creator feedback rewrites.
  • references/evidence-ladder.md for minimum evidence guidance.
  • references/drift-guard-rules.md for scope drift warnings.
  • references/handoff-memory-rules.md for handoff documents.
  • references/project-profile-template.md for optional project context.

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.