prompt-governance

Imported from borghei/claude-skills (engineering/prompt-governance/SKILL.md). Install upstream with npx skills add borghei/claude-skills --skill prompt-governance. Copyright stays with the author (MIT + Commons Clause).

Prompt Governance

Category: Engineering Domain: AI Governance

Overview

The Prompt Governance skill provides tools for auditing prompts for security vulnerabilities, bias, and safety issues, plus managing a versioned catalog of approved prompts. Essential for organizations deploying LLM-based applications at scale.

Clarify First

Before auditing or cataloging, settle the inputs below. When one is missing or vague and would change the result, ask about it; when it wouldn't, use a sensible default and say which one you used.

• Target prompt(s): the exact file/text to audit or the catalog dir to manage (the subject of every check).
• Task: audit vs catalog management: selects prompt_auditor.py vs prompt_catalog_manager.py and the whole workflow.
• Check focus: injection / bias / safety (sets which auditor checks run and the pass/fail bar).

Ask about the two or three inputs that matter most for this request, not the whole list. If the user wants a result straight away, produce it and state your assumptions at the top.

Quick Start

# Audit a prompt for security and safety issues
python scripts/prompt_auditor.py --file system_prompt.txt

# Audit with specific focus
python scripts/prompt_auditor.py --text "You are a helpful assistant..." --checks injection,bias,safety

# Initialize a prompt catalog
python scripts/prompt_catalog_manager.py --init --catalog-dir ./prompts

# Add a prompt to the catalog
python scripts/prompt_catalog_manager.py --add --name "customer-support-v1" --file prompt.txt --catalog-dir ./prompts

# List all prompts in catalog
python scripts/prompt_catalog_manager.py --list --catalog-dir ./prompts

Tools Overview

Workflows

Prompt Review Process

1. Author writes or modifies a prompt
2. Run prompt_auditor.py for automated checks
3. Review findings and address critical issues
4. Add approved prompt to catalog with prompt_catalog_manager.py
5. Deploy from catalog (never from ad-hoc sources)

Prompt Versioning

1. Store all prompts in the catalog; each --add with changed content gets the next patch version (1.0.0, 1.0.1, ...), and identical content is rejected as a duplicate
2. Use --diff to compare versions before promotion
3. Move the latest version through draft, review, approved and deployed with --status; keep the catalog directory in version control for the audit trail
4. There is no rollback command, and re-adding an earlier version's text is rejected as a duplicate. To roll back, redeploy the previous version's text from versions/<name>_v<x_y_z>.txt and mark the bad latest version retired with --status retired (the CLI changes the latest version only)

Scope & Limitations

In Scope:

• Pattern-based audit of a prompt with prompt_auditor.py across four check groups: injection, bias, safety and quality, selectable with --checks.
• A local, file-based prompt catalog with prompt_catalog_manager.py: init, add with automatic version numbers and a content hash, list, search, diff between versions, and status changes (draft, review, approved, deployed, retired).
• The prompt review and versioning workflows, and the policies, audit categories, severity levels, catalog schema and review checklist in references/prompt-governance-framework.md.

Out of Scope:

• Testing a deployed model or application against live injection or jailbreak attempts (see engineering/ai-security/).
• Measuring output quality or task accuracy of a prompt (see engineering/agentic-evaluation-framework/).
• Writing or tuning prompts (see engineering/senior-prompt-engineer/) and reducing token cost (see engineering/llm-cost-optimizer/).
• Regulatory AI governance such as the EU AI Act or ISO/IEC 42001 (see ra-qm-team/eu-ai-act-specialist/ and ra-qm-team/iso42001-ai-management/).
• Serving prompts to an application or rolling them back at runtime. The catalog records versions and status only.

Important Caveats:

• The auditor matches regular expressions against prompt text. It catches known phrasings, misses reworded or new ones, and can flag harmless text. A clean audit is not evidence that a prompt is safe or unbiased.
• The auditor and the catalog are not linked. New catalog entries are stored with audit status pending, and running the auditor does not update it.
• The catalog is a local directory with a JSON index and no access control, locking or signing. Approval and audit trail depend on the user's own version control and review process.

Reference Documentation

• Prompt Governance Framework - Policies, review processes, and compliance requirements

Common Patterns

Prompt Lifecycle

Draft -> Audit -> Review -> Approve -> Deploy -> Monitor -> Retire

Governance Checklist

• No injection vulnerabilities
• No harmful content generation potential
• Appropriate bias mitigation
• Clear scope boundaries
• Output format constraints
• Error handling instructions