AgentSkillsCN

lint-markdown

使用基于分类法的分类和自定义规则执行Markdown验证。当需要验证Markdown符合LLM面向写作标准，或生成结构化验证报告时使用。

SKILL.md
--- frontmatter
name: lint-markdown
description: Execute markdown validation with taxonomy-based classification and custom rules. Use when validating markdown compliance with LLM-facing writing standards or when generating structured validation reports.
allowed-tools:
  - Bash(python3)
  - Read
  - Glob
  - Grep

Purpose

Execute Python-based markdown validation with three-tier classification based on taxonomy-rfc.md: STRICT files require full compliance with LLM-facing standards, MODERATE files apply governance rules, and LIGHT files receive basic validation.

IO Semantics

Input: File paths, directories, or global workspace scope with optional parameters.

Output: Structured linting reports with issue categorization, severity levels, and auto-fix suggestions when applicable.

Side Effects: Updates target files when using --fix parameter, generates structured reports in JSON or human-readable format.

Deterministic Steps

1. Environment Validation

  • •Verify Python 3 availability.
  • •Confirm validator script exists at skills/llm-governance/scripts/validator.py.
  • •Validate config.yaml exists and loads properly.

2. File Classification

  • •Apply STRICT classification to LLM-facing files: commands//*.md, skills//SKILL.md, agents//AGENT.md, rules//*.md, AGENTS.md, CLAUDE.md
  • •Apply MODERATE classification to governance files: governance//*.md, config-sync//.md, agent-ops/**/.md
  • •Apply LIGHT classification to remaining markdown files.
  • •Exclude human-facing docs: docs/, examples/, tests/, ide/

3. Validation Execution

  • •Run Python validator based on requested mode: python3 skills/llm-governance/scripts/validator.py <directory> for standard validation python3 skills/llm-governance/scripts/validator.py <directory> for JSON output (future)
  • •Parse validator output and categorize issues by severity and type.

4. Report Generation

  • •Aggregate results by file classification and issue type.
  • •Generate structured summary with:
    • •Total issue count and severity breakdown
    • •Classification-specific compliance metrics
    • •Auto-fix success rate where applicable
  • •Provide actionable recommendations organized by priority.

5. Validation Compliance

  • •Ensure all processing respects skills/llm-governance/rules/99-llm-prompt-writing-rules.md constraints.
  • •Apply imperative communication patterns in all output.
  • •Maintain 100-character line limits in generated reports.

Safety Constraints

  • •Never modify files without explicit --fix parameter.
  • •Preserve original file content through backup mechanisms when fixing.
  • •Respect file exclusions and never scan excluded directories.
  • •Validate tool chain compatibility before executing validator.