Agent readiness - role promotion review
Decide whether an agent is ready for a specific role. The unit of review is not "is this model good"; it is "is this agent-runtime-role combination ready for this responsibility."
Readiness dimensions
- Role fit: primary author, reviewer, worker delegate, tiebreaker, release agent, headless runner, or specialist.
- Capability evidence: successful tasks, failed tasks, live smoke tests, benchmarks, and known weak spots.
- Runtime health: CLI availability, auth state, version currency, quotas, cost model, non-interactive behavior, and timeout handling.
- Tool boundary: filesystem, network, browser, MCP, shell, credentials, write access, and sandbox behavior.
- Governance: review independence, merge/tag authority, compliance trace obligations, escalation rules, and CODEOWNERS/operator gates.
- Reliability: retries, failure signatures, audit logs, resumability, handoff quality, and fallback agent.
- Cost posture: when to use a cheaper model, when the capability justifies cost, and when to avoid fan-out.
Workflow
- Name the exact role and scope being proposed.
- Collect current evidence from local docs, runtime checks, CI, prior PRs, or recent handoffs.
- Compare capability needs against known agent strengths and constraints.
- Identify the minimum pilot or smoke test needed if evidence is incomplete.
- Decide whether the agent can hold the role now, hold it with conditions, or should stay out of the path.
Verdicts
- APPROVE-ROLE: ready for the named scope.
- APPROVE-WITH-CONDITIONS: ready only with explicit guardrails or a pilot.
- DO-NOT-PROMOTE: gaps are material enough to keep the role elsewhere.
- NEEDS-OPERATOR: authority or risk acceptance is outside agent scope.
Output shape
Agent readiness:
- Agent/runtime:
- Proposed role:
- Evidence reviewed:
- Strengths:
- Gaps:
- Required guardrails:
- Cost posture:
- Verdict:
Anti-patterns
- Promoting an agent because it succeeded once on a task outside the target role.
- Confusing model capability with runtime readiness; auth, tools, and non-interactive behavior matter.
- Assigning review authority to an agent that is not independent from the author or artifact.
- Ignoring cost because the most capable model is available.
- Letting fallback routes silently pick a weaker or disabled agent without recording the decision.