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Ai Agent Governance And Limits

ASecurity

Use when defining agent budgets, step limits, reversibility, blast-radius controls, kill switches, and governance policy for agentic AI systems.

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  • Added May 27, 2026
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Scanned October 1, 2026

npx -y skills add peterbamuhigire/skills-web-dev --skill ai-agent-governance-and-limits --agent claude-code

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SKILL.md
---
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.

<!-- dual-compat-start -->

## 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](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](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](references/routing.md) maps retired child skill slugs to their consolidated reference folders.
- Load [references/agent-governance-and-oversight.md](references/agent-governance-and-oversight.md) when deciding code-versus-model split, deferral to humans, safeguard components, agent registry, readiness, or NIST AI RMF evidence mapping.

## Consolidated Child References

- Load [references/routing.md](references/routing.md) to map retired AI child skill slugs to their reference modules.
## Evidence Produced

| Category | Artifact | Format | Example |
| --- | --- | --- | --- |
| Security | Agent limits and reversibility register | Markdown table | step budget, blast radius, approval tier, kill path, and drill result |

<!-- dual-compat-end -->
## Inputs

| Artefact | Required? | Purpose |
|---|---|---|
| Agent task and tool catalogue | yes | Identify actions and costs |
| Step, token, time, money, and blast-radius policy | yes | Define limits |
| Escalation and termination policy | yes | Stop unsafe runs |

## Capability contract

Read and search are required. Budget enforcement tests may execute only in controlled environments. Changing production limits or kill switches requires explicit operational authority.

## Degraded mode

Fallback without telemetry or enforcement access: produce the limit policy and gap register; do not claim limits are enforced.

## Decision rules

| Limit event | Runtime response | Failure avoided |
|---|---|---|
| Soft threshold reached | Warn, checkpoint, or degrade | Abrupt failure |
| Hard cost/step/time threshold reached | Stop safely and preserve state | Runaway execution |
| Blast-radius or policy boundary reached | Deny and escalate | Unsafe autonomy |

## Domain anti-patterns

- Limits documented only in prompts. Fix: enforce outside the model.
- One global budget for every tenant and task. Fix: scope by risk and entitlement.
- Retrying after a hard limit. Fix: require continuation authority.
- Kill switch without state preservation. Fix: checkpoint and record termination reason.
- Measuring attempted steps as completed value. Fix: separate attempts and success.

Files in this skill

  • SKILL.md2.7 KB
  • references/ai-agent-cost-and-step-budgets/entrypoint.md11.7 KB
  • references/ai-agent-cost-and-step-budgets/references/budget-enforcement-pipeline.md7.6 KB
  • references/ai-agent-reversibility-and-blast-radius/entrypoint.md9.9 KB
  • references/ai-agent-reversibility-and-blast-radius/references/dry-run-patterns.md6.5 KB
  • references/ai-agent-reversibility-and-blast-radius/references/transactional-group-patterns.md6.5 KB
  • references/routing.md693 B

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