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Agent Skill · 研究检索

create-work-item(创建工作项)

create-work-item 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。

create-work-item 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 69,087。

总安装 220周安装 9GitHub Stars 公开资料未说明下载 71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:create-work-item(创建工作项)
来源仓库:https://github.com/squirrel289/pax
仓库路径:skills/create-work-item
安装命令:
npx skills add https://github.com/squirrel289/pax --skill create-work-item
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/squirrel289/pax --skill create-work-item

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。

该技能用于创建工作项(如功能、缺陷、实验等),以结构化方式记录目标、依赖和验收标准。适合在启动新功能、拆解史诗任务或定义实验性工作时创建标准化 backlog 条目。通过命令行生成 YAML 格式的工作项文件,保存在 /backlog/ 目录下,便于后续追踪。

安装方式:GitHub 仓库,使用 npx 命令添加;注意权限范围和是否会写入本地文件系统。create-work-item 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/create-work-item

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/squirrel289/pax --skill create-work-item;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

create-work-item 怎么安装?

在终端执行 npx skills add https://github.com/squirrel289/pax --skill create-work-item。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

create-work-item 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。

create-work-item 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。

create-work-item 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。

create-work-item 用的人多吗?

公开数据是累计安装 220 次,近一周安装 9 次,下载 71 次。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。

create-work-item 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
create-work-item

创建工作项 · 本页

220—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

Create Work Item

Overview

Create a new work item (backlog entry) in /backlog/ with consistent structure, YAML metadata, and conventions. Work items track features, bugs, spikes, and tasks with clear goals, dependencies, and acceptance criteria.

When to Use

Create a work item when:

  • Starting a new feature, spike, or task
  • Documenting a well-scoped request or bug
  • Breaking down larger epics into tracked subtasks
  • Proposing architectural changes or experiments
  • Establishing clear success criteria before implementation

When NOT to Use

Skip work items for:

  • Trivial one-off fixes (can be done directly)
  • Exploratory work without clear scope (start with spike first)
  • Time-critical hotfixes (commit directly, backlog after)
  • Duplicate items (update existing instead, see update-work-item skill)

Work Item Lifecycle

Created (not_started)
    ↓
Implementation (in_progress)
    ↓
Review + Testing (testing)
    ↓
Completed (completed)
    ↓
Archived (to archive/)

Backlog Structure

Directory: /backlog/ (current items) or /backlog/archive/ (completed/superseded)

Naming Convention: <number>_<slug>.md where:

  • <number>: Sequential integer (e.g., 54, 55, 56)
  • <slug>: Kebab-case description (e.g., complete_temple_native, implement_adapter_spec)

Numbering: Continue from highest existing number in /backlog/ (not archive)

File Structure

1. YAML Frontmatter

---
title: "Human-readable work item title"
id: <number>
status: not_started | in_progress | testing | completed
state_reason: null  # Set only when status = completed (success | obsolete | redundant | superseded | cancelled)
priority: low | medium | high | critical
complexity: low | medium | high
estimated_hours: <number>
actual_hours: null  # Set when completed
completed_date: null  # Set when completed
related_commit: []  # Array of commit hashes/refs
test_results: null  # URL or description of test results
dependencies:
  - "[[<other_item_number>_<slug>.md]]"
related_backlog:
  - "archive/<number>_<slug>.md"
related_spike:
  - "archive/<number>_<slug>.md"
notes:
  - timestamp: 2024-06-01T12:00:00Z
    user: @john
    note: |
      Optional additional context or implementation notes
---

2. Content Sections

## Goal

One-paragraph summary of what this work item achieves. Answer: "What is the end state?"

## Background

Context, motivation, or prior work. Answer: "Why are we doing this?"

## Tasks

Numbered list of implementation steps or subtasks:

1. **Task Name**: Brief description
   - Sub-point if needed
   - Code example if helpful

2. **Next Task**: Description

## Deliverables

What artifacts or code changes will result:

- New file/module: `path/to/file.py`
- Modified behavior: "CLI now accepts --flag"
- Documentation: "Updated architecture guide"

## Acceptance Criteria

Clear, verifiable markers of completion:

- [ ] All new tests pass (test_*.py)
- [ ] Code coverage > 80%
- [ ] Documented in docs/ (README or ADR)
- [ ] Reviewed and merged to main

Workflow: Creating a Work Item

1. Determine Next ID

  • Check highest numbered file in /backlog/ (not archive)
  • Next ID = max existing + 1

Example: If 56_jinja2_adapter_prototype.md is highest, next = 57_*

2. Draft Frontmatter

---
title: "Implementation feature name"
id: 57
status: not_started
state_reason: null
priority: high  # or medium/low/critical
complexity: medium  # or low/high
estimated_hours: 24
actual_hours: null
completed_date: null
related_commit: []
test_results: null
dependencies:
  - "[[54_complete_temple_native.md]]"  # Links to other work items
related_backlog:
  - "archive/06_rendering_engine.md"  # If refining prior work
notes:
  - timestamp: 2024-06-01T12:00:00Z
    user: @john
    note: Any additional context or decision points
---

Status Values:

  • not_started: Ready to begin
  • in_progress: Active work
  • testing: Implementation done, awaiting review/test results
  • completed: Finished (may have different reasons—see state_reason)

state_reason (used only when status: completed):

  • success: Work completed successfully, all criteria met
  • obsolete: Item no longer relevant (market/approach changed)
  • redundant: Duplicate of another work item
  • superseded: Made moot by another item (note which one)
  • cancelled: Work stopped, won't implement (note why)

Priority:

  • low: Nice-to-have, can be deferred
  • medium: Standard work item
  • high: Important, plan next
  • critical: Blocking other work

Complexity:

  • low: ≤6 hours, isolated change
  • medium: 6-20 hours, affects multiple areas
  • high: 20+ hours, architectural or cross-cutting

3. Write Goal Section

One sentence to one paragraph:

## Goal

Implement `FilterAdapter` interface in the core temple package to provide built-in filters for data transformation: `selectattr`, `map`, `join`, `default`, with type annotations.

4. Add Context Sections

Background: Why this matters, prior decisions, linked research

## Background

Filter support is required for ADR-003 (adapter architecture). Current prototype has hardcoded filter logic; ADR-005 proposes a pluggable FilterAdapter contract. This work implements the concrete contract in `temple/sdk/adapter.py` with 4 core filters and test coverage.

Tasks: Numbered, actionable steps

## Tasks

1. **Design FilterAdapter contract**
   - Extend `temple/sdk/adapter.py` with `FilterAdapter` class
   - Define `apply(input: Any, filter_name: str, args: List) -> Any`
   - Create `FilterSignature` with type hints

2. **Implement core filters in FilterRegistry**
   - `selectattr(objects, attr, value)` → List[T] where T.attr == value
   - `map(objects, attr)` → List[extracted]
   - `join(items, separator)` → str
   - `default(value, fallback)` → value if truthy else fallback

3. **Add type annotations and validation**
   - Each filter registers `FilterSignature` with parameter types
   - Validate filter arguments at parse time

4. **Write unit and integration tests**
   - Test each filter behavior
   - Test error cases (type mismatches, missing attributes)

5. Add Deliverables

## Deliverables

- `temple/sdk/adapter.py` extended with `FilterAdapter` and `FilterSignature`
- `temple/sdk/filters.py` with core filter implementations
- Unit tests in `tests/test_filters.py` (>80% coverage)
- Integration test in `tests/test_renderer_filters.py`
- Updated API docs in `docs/ADAPTER_SPEC.md`

6. Add Acceptance Criteria

## Acceptance Criteria

- [ ] All filter functions are type-annotated and pass mypy
- [ ] 100% of filter branches tested (unit + integration)
- [ ] Filters integrate seamlessly with renderer
- [ ] Code review approved
- [ ] Merged to main branch
- [ ] Release notes updated

Examples

Example 1: Feature Work Item

---
title: "Implement JSON Schema validation in template linter"
id: 57
status: not_started
priority: high
complexity: high
estimated_hours: 20
dependencies:
  - "[[54_complete_temple_native.md]]"
  - "[[44_implement_semantic_validation.md]]"
---

## Goal

Add JSON Schema validation to `temple-linter` to catch schema violations in templates at lint time, catching type mismatches and missing required fields before runtime.

...

Example 2: Spike/Research Work Item

---
title: "Evaluate expression engine alternatives for complex filters"
id: 58
status: not_started
priority: medium
complexity: medium
estimated_hours: 16
notes:
  - timestamp: 2024-06-01T12:00:00Z
    user: @john
    note: |
      Spike to evaluate JMESPath vs. custom expression engine for advanced filters.
      Decision will inform ADR-006 (expression language).
---

## Goal

Research and document three expression engine approaches for advanced data filtering in templates, with proof-of-concept for each.

...

Example 3: Bug/Fix Work Item

---
title: "Fix elif grammar parsing edge case"
id: 59
status: not_started
priority: high
complexity: low
estimated_hours: 4
dependencies:
  - "[[54_complete_temple_native.md]]"
---

## Goal

Fix parser to correctly handle consecutive `{% elif %}` blocks without requiring `{% else %}` at the end.

## Tasks

1. Add test case for multiple elif without else
2. Update grammar in `token_parser.py`
3. Verify fixture tests pass

## Acceptance Criteria

- [ ] Edge case test passes
- [ ] No regression in existing tests
- [ ] Merged to main

Tips & Conventions

Dependency Linking

Link to related work items using [[filename]] syntax:

dependencies:
  - "[[54_complete_temple_native.md]]"
  - "[[43_implement_template_syntax_validation.md]]"

The double-bracket syntax creates wiki-link references that tools can parse.

Commit Tracking

Record commits that implement this work:

related_commit:
  - 6d8c044  # feat(parser): canonicalize control-flow end tokens
  - f00459b  # fix(renderer): handle filter signature validation

Add these incrementally as work progresses, then complete the item.

Effort Estimation

Use fibonacci-like estimates:

  • 1-2 hours: Trivial fixes
  • 4-6 hours: Small feature or bug
  • 8-12 hours: Medium feature
  • 16-24 hours: Large feature
  • 32+ hours: Epic or major refactor

Positioning in Backlog

Not all work needs an item:

  • Skip for: Inline changes, trivial docs fixes, emergency hotfixes
  • Create for: Features, spikes, architectural changes, tracked bugs

When in doubt, create the item—it's easier to abandon than to recreate.

Archiving

When a work item is completed:

  1. Move file from /backlog/ to /backlog/archive/
  2. Set completed_date: YYYY-MM-DD
  3. Ensure actual_hours is recorded
  4. Document related_commit with all implementation commits

Example: After completing #57, move 57_implement_json_schema_validation.md to archive/57_implement_json_schema_validation.md

Related Skills

  • update-work-item: For changing status, effort, and adding test results during work
  • feature-branch-management: Automatically invoked by update-work-item to create feature branches
  • create-pr: Automatically invoked to create pull requests when item status → testing
  • handle-pr-feedback: For addressing PR review feedback
  • finalize-work-item: For completing and archiving items after PR merged
  • git-commit: For recording implementation commits that reference work items

平台分布

Codex

35.89%
按下载量换算25

Claude

29.14%
按下载量换算21

Cursor

17.48%
按下载量换算12

Gemini CLI

8.29%
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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