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飞书项目(Meego/Meegle)操作工具。支持查询和管理工作项、节点流转、视图查询、个人待办、排期统计等功能。 Use when user needs to work with Feishu/Lark Meego project management — including querying work items, creating/updating work items, completing workflow nodes, checking views, listing todos, analyzing schedules/workloads, or searching with MQL. 关键词:飞书项目、meego、meegle、工作项、需求、任务、缺陷、排期、视图、待办、节点。 --- # 飞书项目 (Meego/Meegle) 操作指南 本技能通过 Meegle CLI来操作飞书项目数据。输出语言跟随用户输入语言,默认中文。 > 各命令的调用示例见 [references/api-examples.md](references/api-examples.md)。 > **授权流程**(所有业务命令前必须执行):见 [references/auth-guard.md](references/auth-guard.md) > **CLI 使用指南**(命令结构、参数传递、命令发现):见 [references/cli-guide.md](references/cli-guide.md) --- ## Project 空间域 ### project search 搜索空间信息,将空间名转换为 project_key 或验证空间是否存在。 | 参数 | 类型 | 必填 | 说明 | |------|------|------|------| | --project-key | string | 是 | 空间 projectKey、simpleName 或空间名称 | --- ## WorkItem 工作项域 > 元数据查询命令(`workitem meta-types` / `workitem meta-fields` / `workitem meta-roles` / `workitem meta-create-fields`)的参数表见 [references/workitem.md](references/workitem.md)。 ### workitem create 创建工作项实例。**务必先用 `workitem meta-fields` 获取字段信息,`workitem meta-roles` 获取角色信息。模板 ID 是必填项。** | 参数 | 类型 | 必填 | 说明 | |------|------|------|------| | --work-item-type | string | 是 | 工作项类型 | | --project-key | string | 否 | 空间标识 | | --fields | array | 否 | 字段值列表,每项含 field_key 和 field_value | ### workitem get 按 ID/名称查询工作项概况。不传 fields 时仅返回固定基础字段;如需自定义字段数据,先调 `workitem meta-fields` 获取字段 key 后传入 fields。 | 参数 | 类型 | 必填 | 说明 | |------|------|------|------| | --work-item-id | string | 是 | 工作项 ID 或名称 | | --project-key | string | 否 | 空间 key | | --fields | array | 否 | 要查询的 field_key 或 field_name | ### workitem batch-get 批量查询工作项(Meegle CLI 客户端 fan-out:并发调用 `workitem get`)。单次 ≤ 200 个 ID,3 并发,返回 `{results, errors, summary}`;ID 量大时用 `--format ndjson` 流式输出。 | 参数 | 类型 | 必填 | 说明 | |------|------|------|------| | --work-item-ids | array | 二选一 | 工作项 ID 列表(逗号分隔或多次传入) | | --ids-file | string | 二选一 | 从文件读取 ID(一行一个,`#` 开头注释) | | --fields | array | 否 | 要查询的 fi
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Skill File Structure Sample (Reference)
skill-sample/
├─ SKILL.md ⭐ Required: skill entry doc (purpose / usage / examples / deps)
├─ manifest.sample.json ⭐ Recommended: machine-readable metadata (index / validation / autofill)
├─ LICENSE.sample ⭐ Recommended: license & scope (open source / restriction / commercial)
├─ scripts/
│ └─ example-run.py ✅ Runnable example script for quick verification
├─ assets/
│ ├─ example-formatting-guide.md 🧩 Output conventions: layout / structure / style
│ └─ example-template.tex 🧩 Templates: quickly generate standardized output
└─ references/ 🧩 Knowledge base: methods / guides / best practices
├─ example-ref-structure.md 🧩 Structure reference
├─ example-ref-analysis.md 🧩 Analysis reference
└─ example-ref-visuals.md 🧩 Visual reference
More Agent Skills specs
Anthropic docs: https://agentskills.io/home
SKILL.md Requirements
├─ ⭐ Required: YAML Frontmatter (must be at top)
│ ├─ ⭐ name : unique skill name, follow naming convention
│ └─ ⭐ description : include trigger keywords for matching
│
├─ ✅ Optional: Frontmatter extension fields
│ ├─ ✅ license : license identifier
│ ├─ ✅ compatibility : runtime constraints when needed
│ ├─ ✅ metadata : key-value fields (author/version/source_url...)
│ └─ 🧩 allowed-tools : tool whitelist (experimental)
│
└─ ✅ Recommended: Markdown body (progressive disclosure)
├─ ✅ Overview / Purpose
├─ ✅ When to use
├─ ✅ Step-by-step
├─ ✅ Inputs / Outputs
├─ ✅ Examples
├─ 🧩 Files & References
├─ 🧩 Edge cases
├─ 🧩 Troubleshooting
└─ 🧩 Safety notes
Why SkillWink?
Skill files are scattered across GitHub and communities, difficult to search, and hard to evaluate. SkillWink organizes open-source skills into a searchable, filterable library you can directly download and use.
We provide keyword search, version updates, multi-metric ranking (downloads / likes / comments / updates), and open SKILL.md standards. You can also discuss usage and improvements on skill detail pages.
Keyword Search
Version Updates
Multi-Metric Ranking
Open Standard
Discussion
Quick Start:
Import/download skills (.zip/.skill), then place locally:
~/.claude/skills/ (Claude Code)
~/.codex/skills/ (Codex CLI)
One SKILL.md can be reused across tools.
FAQ
Everything you need to know: what skills are, how they work, how to find/import them, and how to contribute.
1. What are Agent Skills?
A skill is a reusable capability package, usually including SKILL.md (purpose/IO/how-to) and optional scripts/templates/examples.
Think of it as a plugin playbook + resource bundle for AI assistants/toolchains.
2. How do Skills work?
Skills use progressive disclosure: load brief metadata first, load full docs only when needed, then execute by guidance.
This keeps agents lightweight while preserving enough context for complex tasks.
3. How can I quickly find the right skill?
Use these three together:
Semantic search: describe your goal in natural language.
Multi-filtering: category/tag/author/language/license.
Sort by downloads/likes/comments/updated to find higher-quality skills.
4. Which import methods are supported?
Upload archive: .zip / .skill (recommended)
Upload skills folder
Import from GitHub repository
Note: file size for all methods should be within 10MB.
5. How to use in Claude / Codex?
Typical paths (may vary by local setup):
Claude Code:~/.claude/skills/
Codex CLI:~/.codex/skills/
One SKILL.md can usually be reused across tools.
6. Can one skill be shared across tools?
Yes. Most skills are standardized docs + assets, so they can be reused where format is supported.
Example: retrieval + writing + automation scripts as one workflow.
7. Are these skills safe to use?
Some skills come from public GitHub repositories and some are uploaded by SkillWink creators. Always review code before installing and own your security decisions.
8. Why does it not work after import?
Most common reasons:
Wrong folder path or nested one level too deep
Invalid/incomplete SKILL.md fields or format
Dependencies missing (Python/Node/CLI)
Tool has not reloaded skills yet
9. Does SkillWink include duplicates/low-quality skills?
We try to avoid that. Use ranking + comments to surface better skills:
Duplicate skills: compare differences (speed/stability/focus)
Low quality skills: regularly cleaned up