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.
Scanned 9/12/2026
Install to Claude Code
npx -y skills add aibot88/sec_skill_store --skill lint-markdown --agent claude-codeInstalls into .claude/skills of the current project.
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---
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.Is this your skill, or is something wrong with this listing? Request removal or report an issue. Author removals are honored within 72 hours.
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