From m2ai-skills-pack
Interview the user about their agent usage patterns and risk tolerance, then generate a tiered action-class policy document. Each tier gets classification criteria, required approvals, rollback procedures, and monitoring expectations. Use when someone says "/action-class-policy", "define action classes", "agent permissions policy", "what actions can my agent take unsupervised", or wants a governance framework for agent autonomy.
How this skill is triggered — by the user, by Claude, or both
Slash command
/m2ai-skills-pack:action-class-policyThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Produces a tiered action-class policy that governs what agents can do at each autonomy level. Not every agent action carries the same blast radius — this skill makes that explicit and codified.
Produces a tiered action-class policy that governs what agents can do at each autonomy level. Not every agent action carries the same blast radius — this skill makes that explicit and codified.
Use when the user says "/action-class-policy", "define action classes", "agent permissions policy", "agent governance", "what can my agent do without asking", "blast-radius tiers", or wants to establish a structured approval framework for agent workflows.
Ask the user the following questions (one at a time, not a wall of questions):
Collect enough context to calibrate the tier thresholds. Do not proceed to Phase 2 until you have at least answers to questions 1 and 2.
Generate a four-tier taxonomy calibrated to the user's systems. Default taxonomy (customize based on answers):
Produce a action-class-policy.md in the following format:
# Action-Class Policy
Generated: [date]
System scope: [list of systems from Phase 1]
## Tier 0 — Read-Only
Criteria: [user-specific criteria]
Approval: None
Examples: [user-specific examples]
Rollback: N/A
## Tier 1 — Write with Review
Criteria: [user-specific criteria]
Approval: [specific approval mechanism]
Rollback: [specific rollback steps]
Monitoring: [specific monitoring]
## Tier 2 — Production Mutation
Criteria: [user-specific criteria]
Approval: [specific approval mechanism]
Rollback: [specific rollback steps]
Monitoring: [specific monitoring]
## Tier 3 — Infrastructure Change
Criteria: [user-specific criteria]
Approval: [specific approval mechanism]
Rollback: [specific rollback steps]
Monitoring: [specific monitoring]
## Classification Guide
When uncertain which tier an action belongs to, default to the higher tier.
[User-specific edge cases from Phase 1 answers]
## Review Schedule
This policy should be reviewed when: a new system is added, a new agent role is created,
an incident occurs, or quarterly (whichever comes first).
After delivering the policy document, offer concrete integration steps:
PreToolUse hooks that check an action against its tier before executionDerived from Nate Kadlac newsletter (2026-05-25): "AI made your app teams 10x faster. Nobody gave your platform team 10x the headcount." — "not every task an agent does carries the same weight" action-class principle, and PromptKit "Action-Class and Blast-Radius Policy Builder" prompt spec.
npx claudepluginhub m2ai-portfolio/m2ai-skills-pack --plugin m2ai-skills-packGuides creation, editing, and verification of skills for AI coding agents using test-driven development with subagent scenarios. Use when authoring or debugging skills.