Purpose
Enforce LLM content governance for all LLM-facing files using TERSE mode defaults, rule-driven validation, and deterministic tooling.
Apply rules from skills/llm-governance/rules/99-llm-prompt-writing-rules.md and related governance rule files through standardized validators instead of ad-hoc scripts. Provide operational health reporting, capability matrix generation, and structural compliance checking for agents, skills, commands, and rules.
IO Semantics
Input: LLM-facing markdown and configuration files.
Output: Governance findings, severity classifications, suggested edits, and updated files when explicitly approved by higher-level commands.
Side effects: Backups created by orchestration commands before modifications; no direct writes required when running validation only.
Deterministic Steps
1. Toolchain Validation
- •Use
tool_checker.pyto confirm availability of required tools and select fallbacks. - •Abort governance execution for this skill when critical tools are missing and cannot be replaced safely.
2. Target Selection
- •Select LLM-facing files using directory classification:
- •
commands/**/*.md - •
skills/**/SKILL.md - •
agents/**/AGENT.md - •
rules/**/*.md - •
CLAUDE.md - •
AGENTS.md - •
.claude/settings.json
- •
- •Exclude non LLM-facing directories such as documentation, examples, tests, IDE metadata, and backup directories.
3. Automated Validation
- •Run
python3 skills/llm-governance/scripts/validator.py <directory>across the selected scope. - •Validator uses
skills/llm-governance/scripts/config.yamlas Single Source of Truth (SSOT) for all validation rules. - •For each file, detect:
- •Body bold markers outside code blocks.
- •Emoji and decorative Unicode characters.
- •Narrative paragraphs and conversational patterns.
- •Missing or malformed frontmatter for skills, agents, commands, rules, and memory files.
- •Classify violations by severity using rule definitions from
skills/llm-governance/rules/99-llm-prompt-writing-rules.md.
4. Content Normalization Guidelines
- •Enforce TERSE mode:
- •Rewrite narrative paragraphs into imperative directives.
- •Remove conversational fillers and hedging language.
- •Maintain high information density and precise terminology.
- •Enforce formatting rules:
- •Remove non code bold markers from body content.
- •Remove emoji and non-essential decorative Unicode characters.
- •Preserve code blocks and required technical symbols.
- •Enforce structural rules:
- •Ensure required frontmatter fields and section ordering per directory classification.
- •Normalize heading levels and list formatting for clarity and determinism.
5. Operational Health and Matrix Reporting
- •Generate agent and skill capability matrices using
agent-matrix.shandskill-matrix.shto snapshot capability-level, loop-style, and style coverage. - •Run
structure-check.shto validate taxonomy-rfc compliance (layer: execution annotations, absence of legacy COMMAND.md files). - •Correlate governance findings with operational metadata for health reports and rollback candidate identification.
6. Integration with Orchestration Commands
- •Delegate bulk analysis, candidate generation, backup creation, and writeback decisions to
/llm-governanceandagent:llm-governance. - •Use this skill to interpret validator results, derive rewrite strategies, and keep governance behavior aligned with rule files.
Validation Criteria
- •No body bold markers outside code blocks in LLM-facing files.
- •No emoji or decorative Unicode characters in governed content.
- •Communication is terse, directive, and TERSE-mode compliant.
- •Required frontmatter fields and sections are present for each governed directory classification.
- •All governance violations are either resolved or documented with justification in governance reports.