# AI智能体技能框架 **GitHub**: [4444j99/a-i--skills](https://github.com/4444j99/a-i--skills) | **Gitea**: [mc-skills/4444j99--a-i--skills](http://192.168.0.109:3000/mc-skills/4444j99--a-i--skills) ## 中文摘要 包含101个生产就绪的AI智能体技能模块,涵盖创意、技术、企业和治理领域,支持多智能体运行时和联邦注册表,用于大语言模型的可组合任务编排。 ## 标签 `AI智能体` `技能框架` `多智能体` `编排` `LLM` `Python` --- ## README 原文 [![ORGAN-IV: Taxis](https://img.shields.io/badge/ORGAN--IV-Taxis-e65100?style=flat-square)](https://github.com/organvm-iv-taxis) [![Python](https://img.shields.io/badge/Python-3.10+-3776AB?style=flat-square&logo=python&logoColor=white)](https://www.python.org/) [![License: Apache 2.0](https://img.shields.io/badge/License-Apache%202.0-blue?style=flat-square)](./LICENSE) [![Skills](https://img.shields.io/badge/Skills-101-4CAF50?style=flat-square)](./docs/CATEGORIES.md) # a-i--skills [![CI](https://github.com/organvm-iv-taxis/a-i--skills/actions/workflows/ci.yml/badge.svg)](https://github.com/organvm-iv-taxis/a-i--skills/actions/workflows/ci.yml) [![Coverage](https://img.shields.io/badge/coverage-pending-lightgrey)](https://github.com/organvm-iv-taxis/a-i--skills) [![License: MIT](https://img.shields.io/badge/License-MIT-blue.svg)](https://github.com/organvm-iv-taxis/a-i--skills/blob/main/LICENSE) [![Organ IV](https://img.shields.io/badge/Organ-IV%20Taxis-10B981)](https://github.com/organvm-iv-taxis) [![Status](https://img.shields.io/badge/status-active-brightgreen)](https://github.com/organvm-iv-taxis/a-i--skills) [![Python](https://img.shields.io/badge/lang-Python-informational)](https://github.com/organvm-iv-taxis/a-i--skills) **A composable skill framework for AI agent orchestration** -- 101 production-ready skill modules spanning creative, technical, enterprise, and governance domains, organized into a federated registry with multi-agent runtime support. > Part of [ORGAN-IV: Taxis](https://github.com/organvm-iv-taxis) -- the orchestration and governance layer of the [ORGAN system](https://github.com/meta-organvm). --- ## Table of Contents - [Product Overview](#product-overview) - [Why This Exists](#why-this-exists) - [Orchestration Philosophy](#orchestration-philosophy) - [Technical Architecture](#technical-architecture) - [Installation and Quick Start](#installation-and-quick-start) - [Skill Catalog](#skill-catalog) - [Skill Specification Format](#skill-specification-format) - [Federation Protocol](#federation-protocol) - [Tooling and Scripts](#tooling-and-scripts) - [Cross-Organ Integration](#cross-organ-integration) - [Related Work](#related-work) - [Contributing](#contributing) - [License](#license) - [Author](#author) --- ## Product Overview `a-i--skills` is a structured repository of 101 AI agent skills -- self-contained instruction modules that teach large language models how to perform specialized tasks in a repeatable, composable way. Each skill is a directory containing a `SKILL.md` file with YAML frontmatter (metadata for discovery and activation) and Markdown content (the actual instructions an agent follows). The repository serves three distinct functions: 1. **Skill Library** -- A browsable catalog of 101 skills across 12 categories, from algorithmic art generation to security threat modeling, each with standardized metadata, optional helper scripts, reference documentation, and asset templates. 2. **Orchestration Infrastructure** -- Python tooling for skill validation, registry generation, health checking, and multi-agent bundle distribution. A built-in MCP (Model Context Protocol) server enables runtime skill discovery and planning. 3. **Federation Specification** -- A published protocol that allows third-party skill repositories to be discovered, validated, and consumed by any compatible agent, enabling a decentralized ecosystem of interoperable skill providers. The skills themselves range from beginner-level single-file instructions to advanced multi-file modules with executable scripts, OOXML schema references, and comprehensive troubleshooting guides. Four document-processing skills (DOCX, PDF, PPTX, XLSX) demonstrate production-grade complexity -- these are the same skills that power Claude's native document creation capabilities. ### Key Metrics | Dimension | Value | |-----------|-------| | Total skills | 101 (97 example + 4 document) | | Skill categories | 12 | | Multi-agent runtimes supported | 4 (Claude Code, Codex, Gemini CLI, Claude API) | | Total files | ~3,745 | | Repository size | ~5.2 MB | | Federation schema version | 1.1 (stable) | | Skill spec version | Current | --- ## Why This Exists AI agents are increasingly capable of executing complex, multi-step tasks, but their effectiveness depends heavily on the quality of instruction they receive. A generic prompt produces generic output. A well-structured skill -- with domain-specific vocabulary, explicit constraints, worked examples, and validation criteria -- produces expert-level output repeatedly. The challenge is organizational: how do you manage dozens or hundreds of such skills across multiple agent runtimes, ensure they remain valid as specifications evolve, and enable external contributors to build compatible skills without centralized coordination? This repository answers that question with three architectural decisions: - **Convention over configuration.** Every skill follows the same directory structure and frontmatter schema. No build system, no dependency manager, no runtime framework. A skill is a folder with a Markdown file. - **Validation over trust.** Python scripts enforce naming conventions, frontmatter completeness, link integrity, and cross-reference accuracy. CI runs these checks on every pull request. - **Federation over centralization.** The published federation schema means anyone can build a compatible skill repository. Agents discover skills by scanning for `SKILL.md` files, not by consulting a central registry. --- ## Orchestration Philosophy Within the ORGAN system, ORGAN-IV (Taxis) is the governance and orchestration layer. Its repositories do not create content (that is ORGAN-II, Poiesis) and do not sell products (that is ORGAN-III, Ergon). Instead, ORGAN-IV provides the infrastructure that makes the other organs composable: routing rules, governance protocols, capability registries, and workflow coordination. `a-i--skills` embodies this philosophy in three ways: ### Composability Through Standardization Every skill in the catalog follows an identical structural contract: a `SKILL.md` with required `name` and `description` frontmatter fields, optional metadata for complexity, prerequisites, triggers, inputs, outputs, and side effects. This standardization means any orchestration layer -- whether a human selecting skills manually, an agent reasoning about which skills to activate, or a CI pipeline validating skill quality -- can interact with every skill through the same interface. The `complements` field explicitly declares which skills pair well together, enabling multi-skill workflows. The `includes` field creates bundles -- meta-skills that compose multiple skills into a single installable unit. The `triggers` field provides activation conditions (file-type matching, user intent detection, project context detection) that allow agents to autonomously select relevant skills without explicit human instruction. ### Registry as Governance The `generate_registry.py` script compiles all skill frontmatter into a single `skills-registry.json` file -- a machine-readable manifest of every skill's name, description, category, collection, path, license, complexity, and relationships. This registry serves as a governance artifact: it is the authoritative enumeration of what skills exist, what they claim to do, and how they relate to each other. The `validate_skills.py` script enforces invariants that no individual skill can violate: names must match directory names, descriptions must fall within length bounds, complexity values must come from a fixed vocabulary, side-effect declarations must use recognized terms. This is governance through automated enforcement rather than manual review. ### Multi-Runtime Distribution The `refresh_skill_collections.py` script generates agent-specific bundle directories for Claude Code (`.build/claude/skills/`), Codex (`.build/codex/skills/`), and Gemini CLI (`.build/extensions/gemini/`). Each bundle uses the native discovery mechanism of its target runtime: Claude Code uses a plugin marketplace, Codex uses a `.codex/skills/` directory, Gemini uses extensions. The same source skills are distributed through four different channels without any skill-level modification. This is orchestration in its purest form: a single source of truth, multiple distribution targets, automated synchronization, and zero manual intervention per skill per runtime. --- ## Technical Architecture ### Directory Structure ``` a-i--skills/ ├── skills/ # 97 example skills, organized by category │ ├── creative/ # 13 skills (art, music, design, narrative) │ ├── data/ # 6 skills (pipelines, ML, analytics) │ ├── development/ # 26 skills (code quality, testing, infra) │ ├── documentation/ # 4 skills (READMEs, profiles, standards) │ ├── education/ # 4 skills (tutoring, curriculum, feedback) │ ├── integrations/ # 9 skills (MCP, OAuth, webhooks, SpecStory) │ ├── knowledge/ # 6 skills (graphs, architecture, research) │ ├── professional/ # 11 skills (branding, CVs, proposals) │ ├── project-management/ # 4 skills (roadmaps, requirements, orchestration) │ ├── security/ # 6 skills (threat modeling, compliance, incident response) │ ├── specialized/ # 6 skills (blockchain, gaming, AR, fine-tuning) │ └── tools/ # 6 skills (agent swarms, skill creation, meta-tools) │ ├── document-skills/ # 4 production-grade document skills │ ├── docx/ # Word document creation and editing │ ├── pdf/ # PDF manipulation and form handling │ ├── pptx/ # PowerPoint presentation generation │ └── xlsx/ # Excel spreadsheet processing │ ├── scripts/ # Python tooling │ ├── validate_skills.py # Frontmatter and naming validation │ ├── generate_registry.py # Build skills-registry.json │ ├── refresh_skill_collections.py # Multi-runtime bundle generation │ ├── skill_health_check.py # Reference and script validation │ ├── mcp-skill-server.py # MCP server for runtime skill discovery │ ├── validate_generated_dirs.py # Verify bundle synchronization │ ├── generate_lockfile.py # Dependency lockfile generation │ ├── release.py # Release management │ ├── pr_validation_report.py # PR validation reporting │ └── skill_lib.py # Shared frontmatter parsing utilities │ ├── docs/ # Documentation │ ├── CATEGORIES.md # Full skill catalog by category │ ├── CONTRIBUTING.md # Contribution guidelines │ ├── CHANGELOG.md # Release history │ ├── AGENTS.md # Agent-specific repository guidelines │ ├── ROADMAP.md # Development roadmap │ ├── architecture/ # Repository structure documentation │ ├── api/ # Skill spec, federation schema, activation conditions │ └── guides/ # Getting started, creating skills, contributing │ ├── .build/ # Generated multi-runtime bundles │ ├── claude/skills/ # Claude Code plugin bundle │ ├── codex/skills/ # Codex agent bundle │ ├── direct/ # Direct-access bundle │ ├── extensions/gemini/ # Gemini CLI extensions │ └── skills-registry.json # Machine-readable skill manifest │ ├── .claude-plugin/ # Claude Code plugin marketplace metadata │ └── marketplace.json # Plugin definitions (2 collections) │ └── .github/ # CI/CD and templates ├── workflows/validate.yml # Skill validation on PR ├── ISSUE_TEMPLATE/ # Bug report, feature request, new skill └── PULL_REQUEST_TEMPLATE.md # PR template ``` ### Skill Anatomy Every skill follows this structure: ``` skill-name/ ├── SKILL.md # Required: YAML frontmatter + Markdown instructions ├── scripts/ # Optional: executable Python helpers ├── references/ # Optional: supporting documentation ├── assets/ # Optional: templates, fonts, images └── LICENSE.txt # Optional: skill-specific license ``` The `SKILL.md` frontmatter schema: ```yaml --- name: skill-name # Required: must match directory name description: What this skill does. # Required: 20-600 chars, task-focused license: MIT # Optional: license identifier complexity: intermediate # Optional: beginner | intermediate | advanced time_to_learn: 30min # Optional: 5min | 30min | 1hour | multi-hour prerequisites: [other-skill] # Optional: skills to learn first tags: [keyword1, keyword2] # Optional: discovery keywords inputs: [source-code] # Optional: expected input types outputs: [test-report] # Optional: produced output types side_effects: [creates-files] # Optional: environment changes triggers: # Optional: activation conditions - user-asks-about-testing - file-type:*.test.ts complements: [related-skill] # Optional: pairs well with includes: [skill-a, skill-b] # Optional: bundle composition tier: core # Optional: core | community --- ``` ### Activation Conditions The `triggers` field supports five condition types that enable autonomous skill selection: | Trigger Type | Syntax | Example | |-------------|--------|---------| | User intent | `user-asks-about-` | `user-asks-about-api-design` | | Project file | `project-has-` | `project-has-jest-config-js` | | File type | `file-type:` | `file-type:*.test.ts` | | Command context | `command:` | `command:test` | | Reasoning context | `context: