Agent runtime governance

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 (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 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, 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

Run from this skill directory before declaring changes complete:

python scripts/check.py

Completion criteria:

1. scripts/check.py exits 0.
2. No portable-CLI violations remain under this skill directory.
3. Smoke review covers explicit, implicit, rollout, and negative-control prompts.