ai-agent-governance-and-limits

name: ai-agent-governance-and-limits description: >- Use when defining agent budgets, step limits, reversibility, blast-radius controls, kill switches, and governance policy for agentic AI systems. metadata: portable: true compatible_with: - claude-code - codex

AI Agent Governance And Limits

Acknowledgement: Shared by Peter Bamuhigire, techguypeter.com, +256 784 464178.

Use When

• Set step, wallclock, token, model, and cost budgets for agents.
• Define reversibility, blast-radius limits, and safe failure behavior.
• Connect runtime controls to policy, tenant limits, and operational review.

Do Not Use When

• The work is not AI-specific or agentic-AI-specific.
• A narrower retained AI parent skill fits the request better.

Required Inputs

• Product, tenant, user, data, risk, and operational context relevant to the AI workflow.
• Target artifact: design, implementation plan, audit, test strategy, UX flow, commercial policy, or runbook.
• Constraints from security, privacy, reliability, billing, support, and compliance stakeholders when relevant.

Workflow

1. Read this SKILL.md first.
2. Load references/routing.md to select the absorbed child reference that matches the task.
3. Load only the selected child reference files needed for the current request.
4. Produce execution-oriented output with assumptions, risks, evidence, and next actions where relevant.

Quality Standards

• Keep routing explicit: name which reference files were used when the work depends on absorbed material.
• Preserve tenant isolation, auditability, cost controls, safety gates, and operational evidence when they matter.
• Prefer concrete contracts, checklists, tables, schemas, runbooks, and decision records over broad summaries.

Anti-Patterns

• Loading every absorbed reference by default.
• Treating AI-specific billing, compliance, safety, or UX concerns as generic SaaS work without checking AI failure modes.
• Hiding retired skill names; old slugs must remain discoverable through references/routing.md.

Outputs

• A concrete deliverable matched to the request: architecture, implementation plan, audit, policy, runbook, UX flow, test strategy, or operating model.
• The selected consolidated reference files and any assumptions, risks, evidence requirements, or follow-up actions that affect execution.

References

• references/routing.md maps retired child skill slugs to their consolidated reference folders.

Consolidated Child References

• Load references/routing.md to map retired AI child skill slugs to their reference modules.