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Agent Skill · 研究检索

repo-task-proof-loop(回购任务证明循环)

repo-task-proof-loop 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。

repo-task-proof-loop 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,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 47,601。

总安装 727周安装 30GitHub Stars 672下载 238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:repo-task-proof-loop(回购任务证明循环)
来源仓库:https://github.com/denissergeevitch/repo-task-proof-loop
仓库路径:skills/repo-task-proof-loop
安装命令:
npx skills add https://github.com/denissergeevitch/repo-task-proof-loop --skill repo-task-proof-loop
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/denissergeevitch/repo-task-proof-loop --skill repo-task-proof-loop

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。

repo-task-proof-loop 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。它通过分析仓库结构和内容,帮助 Agent 理解项目上下文并提取关键信息。

可通过 npx skills add 命令从指定 GitHub 仓库安装,具体用法请参考原始 README。安装前建议确认权限范围和维护状态,注意是否触发联网或文件读写操作。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

来源仓库内路径:skills/repo-task-proof-loop

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/denissergeevitch/repo-task-proof-loop --skill…;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

repo-task-proof-loop 怎么安装?

在终端执行 npx skills add https://github.com/denissergeevitch/repo-task-proof-loop --skill repo-task-…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

repo-task-proof-loop 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。

repo-task-proof-loop 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/denissergeevitch/repo-task-proof-loop --skill repo-task-proof-loop 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。

repo-task-proof-loop 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。

repo-task-proof-loop 用的人多吗?

公开数据是累计安装 727 次,近一周安装 30 次,下载 238 次,GitHub 672 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。

repo-task-proof-loop 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

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。
  • 第三方扫描已通过,常见的高风险行为没有命中。

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
repo-task-proof-loop

回购任务证明循环 · 本页

727672执行命令未明确通过

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

Repo Task Proof Loop

Use this skill when the user wants a repeatable, auditable implementation workflow for a non-trivial coding task, especially a feature, refactor, migration, or bug fix that should leave repo-local proof in .agent/tasks/<TASK_ID>/.

All task artifacts created by this workflow must stay inside the repository.

When the examples below mention scripts/task_loop.py, that path is relative to this skill root. Run it while your shell working directory is inside the target repository.

What this skill does

  1. Initializes a strict repo-local task folder under .agent/tasks/<TASK_ID>/
  2. Seeds or updates the required artifact files
  3. Installs project-scoped Codex and Claude subagent templates into .codex/agents/ and .claude/agents/
  4. Updates the repo-root AGENTS.md Codex baseline plus the repo's Claude guide file (CLAUDE.md or .claude/CLAUDE.md) with a managed block that explains the workflow
  5. Guides the agent through a strict loop:

- spec freeze - builder implementation - evidence packing - fresh verification - minimal fix - fresh verification again until PASS

See:

  • references/REFERENCE.md
  • references/COMMANDS.md
  • references/SUBAGENTS.md
  • references/SCHEMAS.md

Commands this skill supports

Treat the following words as commands when the user invokes this skill:

  • init <TASK_ID>: create .agent/tasks/<TASK_ID>/, install or refresh subagent templates, and update AGENTS.md plus the repo's Claude guide file
  • freeze <TASK_ID>: create or refine spec.md from the user task, task file, and repo guidance
  • build <TASK_ID>: implement the task against the frozen spec
  • evidence <TASK_ID>: create or refresh evidence.md, evidence.json, and raw artifacts without changing production code
  • verify <TASK_ID>: run a fresh verifier pass and write verdict.json, plus problems.md when needed
  • fix <TASK_ID>: apply the smallest safe fix set from problems.md, then refresh the evidence bundle
  • run <TASK_ID>: execute the full loop from spec freeze through verification
  • status <TASK_ID>: summarize current artifact status

If the user does not supply a command, infer the next step from repo state:

  • If the task folder does not exist, run init first. If the user clearly wants initialization only, stop there. Otherwise, after init succeeds and .agent/tasks/<TASK_ID>/spec.md exists, continue by re-evaluating repo state in the same turn. Do not overlap init with freeze, build, evidence, verify, fix, validate, status, or subagent work.
  • If spec.md is missing or placeholder-only, do freeze
  • If implementation is not yet complete, do build
  • If evidence is stale or missing, do evidence
  • If no fresh verdict exists, do verify
  • If verdict is not PASS, do fix

Initialization step

Run the bundled initializer from the repository root or current working directory inside the repo:

scripts/task_loop.py init --task-id <TASK_ID>

Optional task seeding:

scripts/task_loop.py init --task-id <TASK_ID> --task-file path/to/task.md
scripts/task_loop.py init --task-id <TASK_ID> --task-text "User task text"

The initializer will:

  • resolve the repo root
  • create .agent/tasks/<TASK_ID>/
  • create all required artifacts, including placeholders under raw/
  • install project-scoped subagent files
  • insert or refresh managed workflow blocks in AGENTS.md and the repo's Claude guide file

For Codex, the initializer keeps its managed workflow block in the repo-root AGENTS.md. Codex also supports AGENTS.override.md and configured fallback guide filenames; nested files closer to the code still take precedence, and this skill intentionally does not overwrite them. If init creates or rewrites AGENTS.md during a running Codex session, start a new Codex session before relying on the updated instructions. Codex snapshots project-doc guidance at session start.

For Claude Code, the initializer keeps its managed workflow block in the repo-root CLAUDE.md. Claude Code also supports .claude/CLAUDE.md, .claude/rules/*.md, and CLAUDE.local.md, but this skill treats root CLAUDE.md as the primary project guide because Claude surfaces it directly.

In Claude Code, if init just wrote or refreshed .claude/agents/* during the current session, do not assume those updated agents are already available mid-session.

Treat init as a serial prerequisite. Never overlap it with freeze, build, evidence, verify, fix, validate, status, or child-agent spawning.

Heavy-task default workflow

For large tasks, keep the user-facing request simple. In Codex, continue serially unless the user explicitly asks for delegation or parallel agent work; after that authorization, the skill can choose the internal child setup automatically when the current product surface supports delegation and the task shape warrants it.

Preferred delegated sequence

  1. Run init <TASK_ID> if needed. Wait for it to finish, then confirm .agent/tasks/<TASK_ID>/spec.md and the repo-local task structure exist before continuing.
  2. Only after init completes, spawn exactly one spec-freezer subagent and wait for it
  3. Spawn exactly one builder subagent and let it implement
  4. Continue with the same builder session for evidence packing
  5. Spawn exactly one fresh verifier subagent and wait for it
  6. If verdict is not PASS, spawn exactly one fixer subagent
  7. Spawn one fresh verifier subagent again
  8. Repeat steps 6-7 until the verifier returns PASS or the user stops the loop

Codex adaptive fan-out

Use this only after the user has explicitly authorized Codex delegation and the task is broad enough to benefit from bounded parallel work. Use the simpler serial sequence above for narrow tasks.

Good fits:

  • multiple independent codebase questions must be answered before the spec is stable
  • implementation can be split into disjoint write scopes
  • proof requires several independent read-only checks across different surfaces

Codex pattern:

  1. init stays serial.
  2. If the task is still ambiguous, fan out up to 3 built-in explorer children in parallel. Give each one a single question, subsystem, or path scope. Wait for them, then freeze the spec.
  3. Spawn one spec-freezer child and wait for it.
  4. Spawn one task-builder child as the integration owner.
  5. If implementation splits cleanly, the parent may also spawn bounded built-in worker children in parallel. Each worker must have explicit file or module ownership and must not write evidence.md, evidence.json, verdict.json, or problems.md.
  6. Use send_input or the equivalent follow-up surface to keep the integration builder alive for evidence packing. The builder remains the single owner of the evidence bundle.
  7. If extra proof is needed, the parent may fan out a small bounded set of read-only explorer children to rerun disjoint checks or inspect separate proof gaps in parallel. Those children may report commands, outputs, and findings, but they do not write verdict.json.
  8. Run exactly one fresh verifier child for each verify pass.

Platform behavior

  • In Codex, keep the normal path serial and auto-mode-first after init. Avoid surfacing delegation internals unless they materially affect the work.
  • In Codex, spawn bounded subagents only when the user explicitly asks for sub-agents, delegation, or parallel agent work.
  • In Codex, once delegation is authorized, the skill may choose the matching child roles and whether to stay one-child-at-a-time or use bounded fan-out. The user should not need to name specific child roles or slash commands.
  • In Codex, child spawning is still an explicit parent-orchestrator action. If the current Codex surface blocks delegation, say so briefly only when it materially affects the work, then continue serially.
  • In Codex, keep the task tree shallow. The parent session should spawn research, builder, fixer, and verifier children directly instead of asking one custom task child to orchestrate more children.
  • In Codex, once delegation is authorized, choose between one-child-at-a-time delegation and bounded fan-out from the frozen spec, repo shape, and current delegation surface. Keep init, evidence ownership, and every verifier pass serialized either way.
  • In Codex, keep helper fan-out modest and wave-based. Prefer up to 3 parallel helper children at once, wait for that wave to finish, then decide the next phase.
  • In Codex, built-in explorer is the first choice for read-only repo discovery and proof probes. Built-in worker is appropriate for bounded disjoint implementation or check reruns when you can assign explicit ownership.
  • In Codex, reuse the live builder child for evidence packing by sending it a follow-up instruction. Verifier passes must use a fresh child or fresh session; do not satisfy verifier freshness by resuming an earlier verifier. Builder and fixer children can be reused or resumed when you intentionally want that context back.
  • In Codex, inspect the current child-thread list before reusing or resuming a child. Use /agent in Codex CLI or any equivalent child-thread inventory surface available in the current Codex product surface.
  • In Codex, the plan/todo checklist UI from update_plan is optional session guidance only. It is useful for live progress display, but it is not the source of truth for this workflow.
  • In Claude Code, the skill should decide whether to stay on the main thread or let the main Claude session auto-delegate the current phase to a matching built-in or project subagent after init. The user should not need to request a specific Claude subagent or delegation mode separately.
  • In Claude Code, TodoWrite or the visible task/todo UI is optional session-scoped progress display only. It can help with live tracking in the current session, but it is not the source of truth for this workflow.
  • In Claude Code, prefer the installed project subagents from .claude/agents/, with descriptions written as proactive trigger conditions for the matching proof-loop phase. Claude's main session routes by the task request, subagent descriptions, and current context, so keep each phase prompt clear in natural language. Reuse the same builder child for the evidence step by default. Only run a fresh builder in evidence-only mode if the original builder session is unavailable or you intentionally discarded it. If init just refreshed .claude/agents/* during the current Claude session, fall back to the main thread or already-visible agents instead of assuming the refreshed ones are available immediately.
  • In Claude Code, keep the orchestration flat: main-session auto-delegation is fine, but the proof-loop workflow agents themselves are leaf roles. The parent session should own the proof-loop phase transitions instead of asking one custom task agent to spawn another.
  • In Claude Code, the canonical durable state is always the repo-local artifact set under .agent/tasks/<TASK_ID>/, especially spec.md, evidence.md, evidence.json, verdict.json, and problems.md.
  • If subagents are unavailable, preserve the same role separation across separate sessions or clear mode changes in the current session.

Use the exact role prompts from references/COMMANDS.md.

Spec freeze requirements

spec.md must contain at least:

  • original task statement
  • explicit acceptance criteria labeled AC1, AC2,...
  • constraints
  • non-goals

It may also include:

  • repo guidance sources
  • verification plan
  • assumptions resolved narrowly from the user request

Do not edit production code during spec freeze.

Evidence packing requirements

evidence.md and evidence.json must judge each acceptance criterion independently with one of:

  • PASS
  • FAIL
  • UNKNOWN

Evidence packing may run missing checks, but it must not keep changing production code.

Every PASS must cite concrete proof such as:

  • file paths
  • commands run
  • exit codes
  • output summaries
  • artifact paths under raw/

Do not claim overall PASS in the evidence bundle unless every acceptance criterion is PASS.

Fresh verification requirements

The verifier must be a fresh session or fresh subagent. In Codex, do not satisfy this requirement by resuming a prior verifier child.

The verifier must judge the current repository state and current rerun results, not the builder narrative.

The verifier writes:

  • .agent/tasks/<TASK_ID>/verdict.json
  • .agent/tasks/<TASK_ID>/problems.md only when overall verdict is not PASS

problems.md must include, for each non-PASS criterion:

  • criterion id and text
  • status
  • why it is not proven
  • minimal reproduction steps
  • expected vs actual
  • affected files
  • smallest safe fix
  • corrective hint in 1-3 sentences

The verifier must not modify production code or backfill the evidence bundle.

Fixer requirements

The fixer reads only:

  • spec.md
  • verdict.json
  • problems.md

The fixer must:

  • reconfirm each listed problem in the codebase before editing
  • make the smallest safe change set
  • avoid regressing already-passing criteria
  • regenerate evidence.md, evidence.json, and raw artifacts
  • stop without writing final sign-off

Validation

Before claiming the workflow is correctly initialized or the artifact set is complete, run:

scripts/task_loop.py validate --task-id <TASK_ID>

Run validate only after init has fully finished. If it reports initialization in progress, wait and rerun it instead of treating that result as stable task failure.

For a quick summary:

scripts/task_loop.py status --task-id <TASK_ID>

Run status only after init has fully finished when you need stable task state. If it reports init_in_progress: true, treat that as a retry-later condition.

Guardrails

  • Keep .agent/tasks/<TASK_ID>/ inside the repo
  • Treat the Codex todo/checklist UI as ephemeral progress only; the durable workflow state lives in .agent/tasks/<TASK_ID>/
  • Never claim task completion unless every acceptance criterion is PASS
  • Separate evaluator and fixer roles
  • Keep Codex fan-out shallow and bounded. Parallel helpers may inform the proof loop, but one builder still owns evidence and one fresh verifier still owns verdict.
  • Keep the verifier fresh
  • Prefer the smallest defensible diffs during fixes
  • Preserve existing user guidance outside the managed blocks in AGENTS.md and the repo's chosen Claude guide file

平台分布

Codex

34.99%
按下载量换算83

Claude

31.02%
按下载量换算74

Cursor

16.66%
按下载量换算40

Gemini CLI

8.89%
按下载量换算21

安全审计

Gen Agent Trust Hub

通过

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/denissergeevitch/repo-task-proof-loop --skill repo-task-proof-loop 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。目前只有一个公开来源,建议同时核对源仓库。

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