Agent Skills

A collection of skills for AI coding agents. Skills are packaged instructions and scripts that extend agent capabilities, following the Agent Skills format.

Available Skills

doom-lint-fix

Use when doom lint reports any doom-lint:* rule errors in markdown or MDX documentation files using @alauda/doom — routes to rule-specific fix guides in the rules/ subdirectory

Use when:

• doom lint reports any doom-lint:* error
• You're fixing lint errors in markdown (.md) or MDX (.mdx) documentation files
• You need to understand what a doom-lint rule expects

jira-epic-to-stories

Automatically parse JIRA epic descriptions and create child stories or jobs. Use this skill when you need to generate Jira issues from a standardized epic description.

Prerequisite: This skill requires the Jira CLI (ankitpokhrel/jira-cli) to be installed and authenticated on the host machine.

Use when:

• Generating stories from an epic key based on the epic's description.
• Parsing "Stories" or "Steps"/"Progression" from an epic to create "Story" or "Job" issues.

Key features:

• Automated Issue Creation: Interfaces with the JIRA CLI to create child issues.
• Robust Parsing: Handles complex formatting like ANSI escape codes and indentation.
• Dry-run Mode: Supports a --dry-run flag to preview issues before creation.

Jira Commands (/jira): This repository also includes standalone scripts and commands in the jira/ directory:

• epic-to-stories.py: A comprehensive Python script to parse an epic and automatically create stories via the Jira CLI.
• epic-to-stories-skill.sh: A shell script demonstrating the automation pattern for creating stories from an epic.
• load.sh: Helper script to load Jira-related functions or environment configurations.

doom-doc-assistant

Repository-first assistant for Doom documentation work. It turns requirements into repository-aligned diagnosis reports, execution plans, and drafts for existing or new documentation.

Use when:

• Converting PRDs or requirements into user-facing documentation.
• Modifying authoritative existing pages or adding focused new scenario documents.
• Analyzing when documentation architecture should stay in place versus be restructured.
• Querying Doom framework terminology or documentation guidelines.

Content shapes supported:

• Overview or introduction
• Quick start
• Concept
• Feature guide
• How-to
• Troubleshooting
• Installation
• Upgrade
• Architecture
• Release notes

Key features:

• Product Standards First: Explicit target repo rules override skill defaults; otherwise built-in product documentation standards govern new docs.
• Stable New-Doc Contract: New product docs use lowercase underscore paths plus weight and English queries.
• English-Only Documentation Content: The skill may discuss plans in English or Chinese, but drafted or revised repository documentation content stays in English.
• Manual Preview Prep: After documentation work in a Doom/Yarn repo, the skill prepares local preview with yarn up @alauda/doom and yarn install, then hands yarn dev to a human reviewer.
• No Default Build Or Translate: yarn build and yarn translate are not automatic validation steps.
• Fixed Output Contracts: Diagnosis Report and Execution Plan include required sections instead of free-form summaries.
• Example-Driven: Leverages real codebase search for placement, ordering, component examples, and non-conflicting local style.
• Scope Control: Distinguishes direct modification, focused addition, and true restructure work.

Installation

Install only doom-doc-assistant:

npx skills add alauda/agent-skills --skill doom-doc-assistant

Install the full skill bundle only if you want every skill in this repository:

npx skills add alauda/agent-skills

Usage

Skills are automatically available once installed. The agent will use them when relevant tasks are detected.

Examples:

• "Update the authoritative operator documentation based on this requirement and prepare it for local preview handoff."
• "Create a new HowTo page under docs/en/... with repository-aligned weight and English queries."

Skill Structure

Each skill follows a modular structure:

• SKILL.md: Core instructions for the agent.
• rules/: Modular knowledge base (domain-specific guidelines).
• templates/: Document templates for standardized scaffolding.
• scripts/: (Optional) Helper scripts for automation.

Development

This project follows the Agentic Mindset—writing declarative, modular instructions that empower AI agents to use their native tools.

See AGENTS.md for the Supreme Guiding Directive on developing new skills:

• Declarative over Imperative: Trust the AI's reasoning.
• Modular Knowledge: Keep instructions lean by using the rules/ directory.
• Leverage Native Tools: Encourage the use of grep, ls, and read_file.
• Example-Driven (RAG): Use real-world code examples as the primary learning source.

Project Context for AI Assistants

This repository includes pre-configured context files to help AI assistants quickly understand the project standards:

• AGENTS.md: The core development manual (read this first).
• GEMINI.md / CLAUDE.md: Entry points for specific AI agents.