agent-runtime-governance

Installation
SKILL.md

Agent Runtime Governance

Design and audit the controls that keep tool-bearing agent systems predictable, observable, and safe to operate.

Scope: Runtime governance for agents that use tools, memory, approvals, subagents, evals, or external systems. NOT for generic vulnerability scanning (security-scanner), normal code review (honest-review), prompt-only optimization (prompt-engineer), or MCP implementation details (mcp-creator).

Dispatch

$ARGUMENTS Mode Action
Empty menu Show governance modes and required inputs
design <system> design Define runtime policies for a new or changing agent system
audit <path-or-system> audit Review existing tool, approval, memory, telemetry, and eval controls
permissions <agent-or-tools> permissions Design allowlists, denylists, approval modes, and escalation rules
memory <agent-or-system> memory Define memory scope, retention, privacy, and invalidation policy
evals <workflow> evals Plan regression, adversarial, and runtime acceptance eval loops
rollout <system> rollout Define staged release, monitoring, rollback, and operator readiness controls
incident <failure-mode> incident Define containment and recovery controls for agent failures
Natural language about agent tools, permissions, memory, evals, or containment Auto-detect the closest mode

Governance Surfaces

Surface Review Questions
Tools Which tools can read, write, spend money, deploy, message users, or delete data?
Approvals Which operations require explicit user approval or human review?
Memory What can be stored, for how long, and at what scope?
State What is durable, replayable, idempotent, and auditable?
Telemetry Which traces, decisions, tool calls, and failures are observable?
Evals Which scenarios prevent regression before rollout?
Containment How does the system stop, rollback, quarantine, or degrade safely?

Canonical Vocabulary

Use these canonical terms exactly when producing governance reports.

Term Meaning
tool consequence The real-world effect a tool call can have: read, write, deploy, message, spend, delete, or expose
approval gate Explicit human or policy checkpoint before a higher-risk action
runtime guard Hook, wrapper, allowlist, denylist, test, or platform policy that enforces a governance rule
memory boundary Scope, retention, redaction, and invalidation policy for stored agent context
containment Stop, rollback, quarantine, or degrade action after unsafe or failed behavior
shadow mode Runtime mode that records proposed actions without executing them

Classification Gate

Classify the request before choosing a mode:

  1. If it asks for app vulnerability scanning, route to security-scanner.
  2. If it asks for code review, route to honest-review.
  3. If it asks for prompt wording only, route to prompt-engineer.
  4. If it asks how to implement an MCP server, route to mcp-creator.
  5. Otherwise, choose the closest runtime governance mode from the dispatch table.

Workflow

  1. Define the agent’s job, users, data sensitivity, and external effects.
  2. Inventory tools by capability: read-only, write, destructive, financial, deploy, messaging, credential access, and network egress.
  3. Map approval gates to consequence, reversibility, and confidence.
  4. Define memory scope, retention, redaction, and invalidation rules.
  5. Require telemetry for tool calls, decisions, approval outcomes, and failures.
  6. Build evals around unsafe tool use, stale memory, missing approval, and failure containment.
  7. Define rollout gates, rollback criteria, and operator evidence for changes that affect live users, accounts, credentials, or external systems.
  8. Return a governance matrix with owners and enforcement points.

Scaling Strategy

Scope Strategy
Single agent or workflow Produce one control matrix and one eval/monitoring set
Multiple agents sharing tools Group by tool consequence and shared approval gates
Platform-wide governance Define baseline policy first, then exceptions by agent class
Live production rollout Add staged rollout, rollback, monitoring, and owner review gates

Progressive Disclosure

  • Start with this SKILL.md for routing and control surfaces.
  • Read references/control-matrix.md for permissions, memory, telemetry, and eval controls.
  • Read references/rollout-governance.md only when release, rollback, monitoring, or production readiness is in scope.
  • Do not load security, prompt, or MCP implementation references unless routing redirects to those skills.

Reference File Index

File Read When
references/control-matrix.md Designing or auditing runtime control surfaces
references/rollout-governance.md Planning staged release, rollback, monitoring, and operator readiness

Output Shape

## Agent Governance Report

- System:
- Mode:
- Risk tier:

### Control Matrix
| Surface | Current | Required | Enforcement | Evidence |
|---|---|---|---|---|

### Required Changes
- ...

### Evals And Monitoring
- ...

### Rollout And Containment
- ...

Critical Rules

  1. Classify tools by consequence before recommending autonomy.
  2. Require explicit approval for irreversible, costly, public, credential, or destructive actions.
  3. Keep memory scope narrow and document retention, redaction, and invalidation.
  4. Require telemetry for tool calls, approvals, denials, failures, and containment actions.
  5. Add evals for unsafe tool use, missing approval, stale memory, and rollback behavior.
  6. Separate policy from enforcement; name the hook, wrapper, test, or runtime gate that enforces each rule.
  7. Do not replace security-scanner, honest-review, prompt-engineer, or mcp-creator; route to them when the request is outside runtime governance.
  8. Do not mark a governance change ready without rollout, rollback, and monitoring criteria.

Validation Contract

Before declaring this skill complete after edits:

uv run wagents validate
uv run wagents eval validate
uv run python audit.py skills/agent-runtime-governance
uv run wagents package agent-runtime-governance --dry-run

Completion criteria:

  • Skill and eval validation pass.
  • Audit score is A or all remaining findings are explicitly accepted.
  • Package dry-run passes.
  • Smoke review covers explicit, implicit, rollout, and negative-control prompts.
Related skills
Installs
3
GitHub Stars
2
First Seen
12 days ago