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Agent Skill · 研究检索

acceptance-criteria-validate(验收标准验证)

acceptance-criteria-validate 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。

acceptance-criteria-validate 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,权限为执行命令;许可证信息还不明确,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 65,745。

总安装 275周安装 11GitHub Stars 2下载 89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
unknown

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:acceptance-criteria-validate(验收标准验证)
来源仓库:https://github.com/giladresisi/ai-dev-env
仓库路径:skills/acceptance-criteria-validate
安装命令:
npx skills add https://github.com/giladresisi/ai-dev-env --skill acceptance-criteria-validate
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 npx skills 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。

skills.shnpx skills
npx skills add https://github.com/giladresisi/ai-dev-env --skill acceptance-criteria-validate

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。

用于检索和筛选与任务相关的信息,帮助定位验收标准或验证依据,提升信息查找效率。适用于需要根据关键词、任务场景或来源线索快速获取候选结果的环境,如代码审查或需求对齐。支持从计划文件、Issue 或协作记录中扫描并提取相关标准,按优先级顺序返回匹配内容。

安装命令:npx skills add https://github.com/giladresisi/ai-dev-env --skill acceptance-criteria-validate 需确认权限范围,避免访问敏感仓库或执行外部命令,防止误读非公开 Issue 或 PR 数据。

来源仓库内路径:skills/acceptance-criteria-validate

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/giladresisi/ai-dev-env --skill acceptance-crit…;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

    它需要执行命令,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

acceptance-criteria-validate 怎么安装?

在终端执行 npx skills add https://github.com/giladresisi/ai-dev-env --skill acceptance-criteria-valid…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

acceptance-criteria-validate 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。

acceptance-criteria-validate 需要什么权限?

权限级别是执行命令。安装流程涉及命令执行,可能通过 npx skills add https://github.com/giladresisi/ai-dev-env --skill acceptance-criteria-validate 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

acceptance-criteria-validate 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

acceptance-criteria-validate 用的人多吗?

公开数据是累计安装 275 次,近一周安装 11 次,下载 89 次,GitHub 2 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。

acceptance-criteria-validate 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

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。

先想清楚的地方

  • 需要执行命令,装到常用环境前要先评估影响面。
  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 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

  • 不能接受 Skill 在你机器上执行命令的人。
  • 需要明确授权才能用到公司项目里的场景。
  • 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
acceptance-criteria-validate

验收标准验证 · 本页

2752执行命令未明确有提醒

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

Acceptance Criteria: Validate

Step 0: Check for Context

If no request, task description, or plan file was provided as context (the skill was invoked with no arguments and nothing in the conversation identifies what was implemented):

  • Output: "This skill needs context to validate against. Please provide the request description, a plan file path, or point me to an acceptance_criteria.md file."
  • STOP — do not continue.

Step 1: Locate Acceptance Criteria

Work through the following sources in order, stopping as soon as criteria are found.

Source 1: Plan file referenced in context

Check whether the context references a plan file (a .md path, usually under .agents/plans/).

If a plan file is identified:

  • Read the entire plan file
  • Search for any of these headings (case-insensitive):

- ## ACCEPTANCE CRITERIA - ## Acceptance Criteria - ## Success Criteria - ## Completion Criteria - ## Done When

  • Also scan the ## COMPLETION CHECKLIST section — individual checklist items there may function as acceptance criteria even if not labeled as such
  • Extract all criteria found. If criteria exist here → proceed to Step 2 with these.

Source 2: acceptance_criteria.md file

If no criteria were found in the plan file, search for acceptance_criteria.md in:

  • .agents/acceptance_criteria.md
  • acceptance_criteria.md (project root)

If found:

  • Read the file
  • Identify whether any section title or context summary matches the current request or feature (by name, date, or description similarity)
  • If a matching section exists → extract its criteria and proceed to Step 2 with these
  • If the file exists but no section matches → note this and continue to Source 3

Source 3: Criteria embedded in the request itself

If neither of the above yielded criteria, re-read the current request (the message that triggered this skill or the broader conversation context). Look for:

  • Explicit "success criteria", "acceptance criteria", or "done when" statements
  • Numbered or bulleted requirements the user stated
  • Phrases like "I expect...", "it should...", "the feature is done when..."

If found in the request → proceed to Step 2 with these.

Source 4: Ask the user

If no criteria were found in any source:

First, derive your own suggested criteria based on the request description and any plan content you have read (apply the same dimension framework as the acceptance-criteria-define skill: functional correctness, error handling, integration/E2E, validation, non-functional, out of scope).

Then use AskUserQuestion:

Question: "I couldn't find any acceptance criteria for this request. Here's what I'd suggest — do these look right, or would you like to define your own?"

Present the suggested criteria in the question context, then offer:

  1. "Use your suggested criteria" — proceed with what you proposed
  2. "I'll define them myself" — wait for the user to provide criteria before continuing

Do not proceed to Step 2 until criteria are confirmed.


Step 2: Validate Each Criterion

For each criterion, investigate whether it has been met. Use a structured approach per criterion:

Investigation methods (use as appropriate per criterion)

Code inspection:

  • Read the relevant source files called out in the plan or implied by the criterion
  • Check for the presence and correct implementation of expected logic, endpoints, functions, or behaviors
  • Verify error handling paths, not just happy paths

Test evidence:

  • Look for test files covering the criterion (unit, integration, or E2E)
  • Check test names and assertions — do they specifically validate the criterion's stated behavior?
  • Note: a passing test suite does not automatically mean a criterion is met if the tests don't cover the specific behavior

Configuration and wiring:

  • For criteria involving config, env vars, or startup wiring: read entry point files (main.py, app.py, etc.) and verify the wiring is actually present, not just documented
  • For criteria involving external services or MCP tools: check URL construction, auth headers, and connection logic

Documentation and artifacts:

  • Check PROGRESS.md for notes indicating the criterion was addressed or explicitly deferred
  • Check .agents/execution-reports/ for any execution report for this feature
  • Check git diff / recently changed files if helpful context is needed

Run validation commands (if safe and appropriate):

  • If the plan's ## VALIDATION COMMANDS section lists commands and it is safe to run them in the current environment, run them and use the results as evidence
  • Do not run commands that could have side effects (migrations, deployments, destructive ops) without confirmation

Deferred demo/script validation — MANDATORY structural probe: When a demo script or CLI is marked UNVERIFIABLE or deferred due to environmental constraints (live server, external auth, human approval step), do NOT accept the deferral without running a structural probe:

  1. python -c "import <module>" — verifies no import/syntax errors
  2. Run the script up to its first blocking dependency (live server call, input(), etc.) — catches encoding errors, misconfigured subprocess invocations, and wiring bugs before the environmental gate
  3. Inspect any new subprocess invocations for inherited env-var hazards (especially CLAUDECODE, PATH, secret vars) Mark as PARTIAL (not UNVERIFIABLE) if these structural checks are skipped. "Covered at unit level" is only a valid deferral for library behavior, never for the executable surface of the deliverable.

Hardcoded HTTP endpoint URLs: For any criterion involving HTTP calls introduced in the feature, verify at least one representative hardcoded URL against the live server's registered routes (e.g., curl -I <url> or check main.py router/mount registrations). A 404 on a newly introduced URL is a FAIL, not UNVERIFIABLE — incorrect URLs cause silent tool-call failures that are very hard to diagnose.

Per-criterion verdict

For each criterion, produce one of:

  • PASS — Evidence clearly shows the criterion is met (cite the specific file, line, test, or output)
  • FAIL — Evidence shows the criterion is not met or was skipped (explain what is missing)
  • PARTIAL — The criterion is partly met but not fully (describe what is done and what is missing)
  • UNVERIFIABLE — Cannot determine from available artifacts whether the criterion is met (explain why — e.g., requires a live service, requires manual observation)

Step 3: Produce the Validation Report

Format the report as follows:

## Acceptance Criteria Validation Report

**Feature / Request:** <short description>
**Plan File:** <path or "none">
**Criteria Source:** <Plan file / acceptance_criteria.md / Request / User-defined>
**Validated:** <date>

---

### Results

| # | Criterion | Verdict | Evidence |
|---|-----------|---------|----------|
| 1 | <criterion text> | PASS / FAIL / PARTIAL / UNVERIFIABLE | <1–2 sentence evidence summary> |
| 2 | ... | ... | ... |

---

### Summary

**PASS:** <n>
**FAIL:** <n>
**PARTIAL:** <n>
**UNVERIFIABLE:** <n>
**Total:** <n>

**Overall verdict:** ACCEPTED / REJECTED / NEEDS REVIEW

- ACCEPTED — all criteria PASS (UNVERIFIABLE items acknowledged)
- REJECTED — one or more criteria FAIL
- NEEDS REVIEW — one or more criteria PARTIAL or UNVERIFIABLE with no other FAILs

---

### Failures & Gaps

<For each FAIL or PARTIAL criterion:>

#### Criterion <#>: <criterion text>

**Verdict:** FAIL / PARTIAL
**What is missing:** <specific description>
**Where to look / fix:** <file path, function, or area of the codebase>
**Suggested next step:** <concrete action — e.g., "Implement X in file Y", "Add test case for Z">

---

### Notes

<Any UNVERIFIABLE items with explanation of what manual verification would require>
<Any observations about gaps in the criteria themselves>

Step 4: Write or Display the Report

If invoked as a background subagent (spawned via the Agent tool from another skill, e.g., from the execute skill's post-execution flow):

  • Always write the report to .agents/acceptance-validations/<feature-name>-validation.md
  • Derive <feature-name> from the plan file name or the request title
  • Return a concise summary to the caller: file path + overall verdict + list of any FAILs or PARTIALs
  • This ensures the orchestrating agent can read the full results even if it cannot see subagent output directly

If the caller requested output to a file (e.g., "save the validation report", "write to a file"):

  • Write the report to .agents/acceptance-validations/<feature-name>-validation.md
  • Derive <feature-name> from the plan file name or the request title
  • Output to the user: "Validation report written to .agents/acceptance-validations/<feature-name>-validation.md."

If the caller requested output to the CLI (default when invoked interactively with no file destination specified):

  • Output the full report directly to the conversation

In all cases, end with one of these verdicts printed prominently:

Overall: ACCEPTED   — all acceptance criteria met, ready for commit/review
Overall: REJECTED   — <n> criteria not met, execution is incomplete
Overall: NEEDS REVIEW — <n> criteria need manual confirmation before accepting

Step 5: Gate on Verdict

If verdict is ACCEPTED:

  • Inform the caller (or the user) that execution is complete and the work meets the defined acceptance criteria
  • If this skill was invoked from within the execute skill flow, return control to that skill to proceed with the Output Report

If verdict is REJECTED or NEEDS REVIEW:

  • Do NOT declare execution complete
  • List the failing or unresolved criteria clearly
  • Ask the user (or return to the calling skill) with: "The following criteria were not met. Should I fix them now, or do you want to review first?" Options:

1. "Fix them now" — proceed to address each FAIL/PARTIAL criterion, then re-run this skill 2. "I'll review first" — stop here and hand control back to the user 3. "Accept anyway" — override and mark as complete despite gaps (user takes responsibility)

Do not silently pass failed criteria.

平台分布

Codex

38.33%
按下载量换算34

Claude

29.4%
按下载量换算26

Cursor

19.54%
按下载量换算17

Gemini CLI

9.45%
按下载量换算8

安全审计

Gen Agent Trust Hub

可疑

Socket

通过

Snyk

通过

权限和风险

执行命令

安装流程涉及命令执行,可能通过 npx skills add https://github.com/giladresisi/ai-dev-env --skill acceptance-criteria-validate 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

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。目前只有一个公开来源,建议同时核对源仓库。

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