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Agent Skill · 研究检索

task-loop(任务循环)

task-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。

task-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,权限为需要联网;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 71,838。

总安装 192周安装 8GitHub Stars 14下载 64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:task-loop(任务循环)
来源仓库:https://github.com/connorads/dotfiles
仓库路径:skills/task-loop
安装命令:
npx skills add https://github.com/connorads/dotfiles --skill task-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/connorads/dotfiles --skill task-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。

task-loop 用于从 backlog 自动生成自包含任务循环目录,包含 PROMPT.md 和 run-log.md 便于交接执行。它适用于无记忆 Agent 场景下的任务自动化流转,支持多轮独立运行。使用时需提供 backlog 文件路径,否则自动查找最近创建的任务清单。

安装前建议确认 Git 忽略规则和日志存储位置权限。task-loop 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/task-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/connorads/dotfiles --skill task-loop;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

    它需要需要联网,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

task-loop 怎么安装?

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

task-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。

task-loop 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

task-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。

task-loop 用的人多吗?

公开数据是累计安装 192 次,近一周安装 8 次,下载 64 次,GitHub 14 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。

task-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

  • 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

  • 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
task-loop

任务循环 · 本页

19214需要联网未明确通过

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

Task Loop

Scaffold a self-contained loop directory from an existing backlog. The directory contains everything a fresh agent session needs to pick up a task, execute it, and hand off to the next iteration — with no session memory between runs.

When to use

Invoke when the user has a backlog (from /task-plan, hand-written, or any structured task list) and wants to run it through an automated agent loop. The output is a directory with PROMPT.md, run-log.md, and a shared.gitignore.

Process

1. Locate the backlog

Accept a backlog file path. If not provided, look for:

  • A file the user recently created or discussed
  • Files matching TASKS/*/backlog.md or *TASKS*.md
  • Any markdown file with checkbox tasks

Ask if unclear.

2. Read and understand the backlog

Read the backlog to understand:

  • Task shape (what fields each task has)
  • Verification patterns (global rules, per-task criteria, referenced docs)
  • Dependencies between tasks
  • Any reference material mentioned in the backlog header

This understanding drives how PROMPT.md is adapted.

3. Ask about execution context

Ask the user:

  • "Are there docs or skills that will help execute these tasks?" (e.g. Figma workflow, testing guide, API docs)
  • "Any project-specific verification rules beyond what's in the backlog?"
  • "What timeout per iteration makes sense?" (helps with the suggested run command)

4. Generate the loop directory

If the backlog is already in a TASKS/<name>/ directory, generate files alongside it. If not, ask where to create the directory or suggest TASKS/<name>/ based on the backlog content.

Generate these files:

PROMPT.md

The loop contract. Self-contained — the agent reads this one file and has the complete protocol. Built from the core protocol template (read references/loop-protocol.md) plus task-specific adaptations:

  • File paths — point to this directory's loop-state.md, run-log.md, and backlog.md
  • Loop completion token — emit __PROMISE_RL_DONE__ as a standalone final line when no unchecked tasks remain so the default rl promise-token handling can stop cleanly. This is the Ralph-loop “completion promise” expressed as a plain token.
  • Verification rules — extracted from the backlog's global and per-task verification patterns. Reference external docs if the backlog mentions them
  • Dependency handling — if the backlog has a dependency graph, add instructions to respect it when picking the next task
  • Reference docs — if the user mentioned helpful docs or skills, add them to the prompt so the agent knows where to look

The prompt must start with a level-1 heading (markdown linter requirement).

run-log.md

Empty file with # Run Log header. Entries are appended by the agent during execution — one entry per completed or blocked task.

Entry format:

## <ISO-timestamp> | <task-id> | <done|blocked>
- **Commit:** <sha>
- **Verification:** <what was run>
- **Surprises:** <anything unexpected, or "none">
TASKS/.gitignore

If a TASKS/.gitignore doesn't already exist in the parent directory, create one containing loop-state.md. This keeps ephemeral state out of version control while allowing clean deletion of the entire task directory.

5. Present the output

Show the user:

  • The generated directory structure
  • The PROMPT.md content (or a summary if long)
  • How to run it, e.g.: rl <n> -t 30m -- claude -p "Read and follow TASKS/<name>/PROMPT.md"

PROMPT.md anatomy

Every generated PROMPT.md has these sections:

  1. Heading — # Prompt
  2. Preamble — "You are running in an automated loop. Read these files before doing anything else:" followed by the three file paths
  3. Protocol — the state machine:

- No state file or status done → append run-log entry, pick next task - No unchecked tasks remain → emit __PROMISE_RL_DONE__ and exit - Status in_progress or verifying → resume from checklist - Status blocked → log blocker, skip to next task

  1. Verification — rules adapted from the backlog, referencing external docs where appropriate
  2. Completion rule — the four conditions that must all be true before marking a task done
  3. Surprises — instructions to capture unexpected findings

Read references/loop-protocol.md for the core template. Adapt it — don't copy it verbatim. Each backlog has different verification needs and reference material.

loop-state.md

Created at runtime by the agent, not pre-created by this skill. The agent creates it when claiming a task. Format:

---
current_task: <task-id>
status: in_progress | verifying | done | blocked
last_commit: ""
next_task: <task-id>
blockers: ""
---

## Checklist

- [ ] Code changes made
- [ ] Verification passed
- [ ] Backlog checkbox updated
- [ ] Commit created

## Surprises

- (none yet)

Gitignored via TASKS/.gitignore — changes every iteration, noisy in version control. Clean deletion of the task directory removes it too.

平台分布

Codex

34.71%
按下载量换算22

Claude

32.58%
按下载量换算21

Cursor

17.56%
按下载量换算11

Gemini CLI

9.27%
按下载量换算6

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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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