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Agent Skill · 研究检索

dot-tasks(点任务)

dot-tasks 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。

dot-tasks 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,权限为只读;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 51,124。

总安装 593周安装 24GitHub Stars 1下载 186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:dot-tasks(点任务)
来源仓库:https://github.com/awni00/dot-tasks
仓库路径:skills/dot-tasks
安装命令:
npx skills add https://github.com/awni00/dot-tasks --skill dot-tasks
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/awni00/dot-tasks --skill dot-tasks

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。

dot-tasks 跟踪本地仓库内的任务生命周期,建议下一步行动。适用于敏捷开发,自动识别待办事项与阻塞点。支持 Plan 与 Execute 模式,生成任务文档与验收标准。需维护 .tasks/ 目录结构,避免与其他系统冲突。dot-tasks 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/dot-tasks

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/awni00/dot-tasks --skill dot-tasks;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

    它标注为只读,先用只读任务试一次,确认行为符合预期再扩大使用范围。

常见问题

6 条

dot-tasks 怎么安装?

在终端执行 npx skills add https://github.com/awni00/dot-tasks --skill dot-tasks。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

dot-tasks 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。

dot-tasks 需要什么权限?

权限级别是只读。该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

dot-tasks 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。

dot-tasks 用的人多吗?

公开数据是累计安装 593 次,近一周安装 24 次,下载 186 次,GitHub 1 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。

dot-tasks 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。
  • 标注为只读权限,试用阶段不容易误改本地文件。

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。
  • 只想先试试效果、不希望它改动本地文件的人。

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
dot-tasks

点任务 · 本页

5931只读未明确通过

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

dot-tasks Skill

dot-tasks is a Python CLI (assumed installed) that tracks human/agent work in a repo-local .tasks/ directory.

Use this skill whenever a repository uses dot-tasks for task lifecycle tracking.

When To Use

  • Use this skill when the user asks for task suggestions based on existing dot-tasks state.
  • Use this skill when the user asks to begin or resume work on an existing task.
  • Use this skill when the user asks for significant new work that should likely be tracked.

Plan Mode Deliverables

By default, when asked to work on a task, produce both artifacts in order:

  1. Develop/refine the task specification and write it to spec.md.
  2. Develop the implementation plan and write it to plan.md.
  • plan.md must be based on a current, user-confirmed spec.md.
  • Exceptions:

- If explicitly asked for spec-only work, produce/update only spec.md. - If resuming from a completed spec.md, validate it is still current, then produce/update plan.md.

  • Artifact scope:

- spec.md: A precise, testable statement of what must be built, including scope, requirements, interfaces, and acceptance criteria. - plan.md: An ordered execution strategy for how to build it, including steps, dependencies, checkpoints, and risk mitigations.

Workflow 1: Suggest What To Work On Next

  1. Discover candidate work:

- Run dot-tasks list todo --json (or dot-tasks list --json if status is not specified). - Inspect likely top candidates with dot-tasks view <task_name_or_id> --json.

  1. Rank candidates using this rubric:

- Higher priority first (p1 before p2, etc). - Prefer unblocked tasks (dependency_health: ready) over blocked work. - Note spec readiness and effort when suggesting tasks to user.

  1. Return the top few options with one-line rationale each.
  2. If high-priority work is blocked, call that out explicitly and include:

- A short unblock path for the blocked item. - A suggested unblocked fallback task.

Workflow 2: Begin Or Resume Existing Task

  1. Resolve the target task:

- If the user provides task_name/task_id, run dot-tasks view <task_name_or_id> --json. - If ambiguous, list likely matches and confirm the target with the user before binding.

  1. Branch by task status:

- doing: resume by reading spec.md, plan.md, and recent activity.md, then continue from the latest checkpoint. - todo: run readiness checks before starting. - done: do not silently restart; ask whether to create a follow-up task or reopen scope explicitly.

  1. Ensure spec is ready before planning implementation
  2. If intent is unclear, ask directed open-ended questions in two stages to clarify intent and develop clear spec. Do not proceed on unstated assumptions when high-level intent is unclear.

Workflow 3: Significant New Work

  1. Detect whether the request is substantial (multi-file, plan-heavy, or likely >=30 minutes).
  2. If substantial, ask whether to create and bind a new dot-tasks task.
  3. If the user agrees:

- Create task with dot-tasks create... (include summary and basic metadata). - Confirm the tracking target and bind work to that task.

  1. If work is quick/simple, do not force task creation unless the user asks.

Shared Task Lifecycle Loop

For tracked task execution (regardless of how it was triggered), follow: create -> spec -> confirm -> start -> plan -> log-activity -> complete

  • Follow Plan Mode Deliverables.
  • Start active execution with dot-tasks start: sets status to doing and creates empty plan.md.
  • If Plan Mode/intent work produced a finalized spec artifact, sync that Markdown to spec.md on the first execution turn after Plan Mode.
  • If Plan Mode produced a finalized <proposed_plan>, sync that Markdown to plan.md on the first execution turn after Plan Mode, after spec confirmation.
  • Keep plan.md current as implementation decisions become concrete.
  • Log meaningful progress with dot-tasks log-activity --note.
  • Log meaningful progress with dot-tasks log-activity --note.
  • For major tasks, document decisions made during implementation in a decisions.md artifact; include key decision rationale and alternative choices considered. Add "# NOTE: " comments in code for significant decisions. For major decisions, pause and ask user for direction before proceeding. Report back to user at end of execution with a summary of decisions made.
  • Use dot-tasks update for mid-flight metadata/scope/priority changes.
  • Before dot-tasks complete, confirm acceptance criteria are satisfied.

Commands

# setup
dot-tasks init                                              # initialize .tasks/

# discover
dot-tasks list --json                                       # list tasks for matching
dot-tasks list [todo|doing|done] --json                    # narrow by status
dot-tasks view <task_name_or_id> --json                    # inspect one task
dot-tasks tags [todo|doing|done] --json                    # tag counts/triage

# lifecycle
dot-tasks create <task_name> --summary "..." --priority [p1|p2|p3|p4] --effort [s|m|l|xl] --tag <tag>
dot-tasks start <task_name_or_id>                          # move to doing + create plan.md
dot-tasks update <task_name_or_id> --priority p1 --effort m --tag backend
dot-tasks log-activity <task_name_or_id> --note "Progress note" [--actor agent]
dot-tasks complete <task_name_or_id>                       # move to done

# maintenance
dot-tasks rename <task_name_or_id> <new_task_name>         # rename task
dot-tasks delete <task_name_or_id>                         # soft-delete to trash

Guardrails

  • Prefer dot-tasks commands over direct edits to task state files.
  • Avoid silent auto-binding on fuzzy matches.
  • Confirm task binding with the user before tracked execution.
  • Apply ordering/default/exception behavior from Plan Mode Deliverables.
  • Direct file edits are allowed for:

1. task.md for writing task summary/specs after dot-tasks create. 2. spec.md: A precise, testable statement of what must be built, including scope, requirements, interfaces, and acceptance criteria. 3. plan.md: An ordered execution strategy for how to build it, including steps, dependencies, checkpoints, and risk mitigations. 4. Other task-local artifacts (for example walkthrough.md, decisions.md, handoff.md) only when useful for scope and naturally produced during the session; confirm with the user before non-trivial additions, and do not manufacture extra artifacts for small/self-contained tasks.

  • Do not rewrite activity.md history; append only.
  • Respect dependency checks.

Data Contract

  • Canonical metadata is in task.md frontmatter.
  • Dependency references use task_id in metadata.
  • Dependencies are displayed to humans as task_name (task_id).
  • activity.md line format is YYYY-MM-DD HH:MM | actor | type | note.

平台分布

Codex

33.41%
按下载量换算62

Claude

30.76%
按下载量换算57

Cursor

18.98%
按下载量换算35

Gemini CLI

8.98%
按下载量换算17

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

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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