mrclrchtr/agent-orchestrator

Agent Orchestrator

Overview

Orchestrate multi-agent work end-to-end: delegate audits and fixes, reconcile results, enforce quality gates, and deliver a validated outcome.

Follow this core pattern: delegate a fresh implementer per cluster, then run a two-stage review (spec compliance first, then code quality).

Non-negotiable rule: never implement changes directly (no coding, no file edits).

Agent Roles

Assume these roles are available in your environment. Do not edit agent definitions or configs. If a required role is missing, stop and ask the operator to configure it.

• architect (design/decisions/contracts)
• auditor (read-only issue finding; no fixes)
• explorer / scout (read-only repo lookup)
• worker (general-purpose helper)
• implementer (code + tests)
• spec_reviewer (read-only, PASS/FAIL: nothing missing, nothing extra)
• quality_reviewer (read-only, PASS/FAIL: maintainability + test quality)

Workflow

1. Use skills when they directly match a subtask

   • If a skill matches the task, invoke it explicitly and follow it (e.g., $web-fetch-to-markdown <url>).
   • When delegating, tell sub-agents which skill to use in their prompt (e.g., “Use $commit for the commit step.”).

2. Freeze scope + success criteria

   • Restate the mission, constraints, and “done” criteria in concrete terms.
   • Identify any authoritative sources (docs/specs) and record what claims must be backed by evidence.

3. Create a phase plan and keep it current

   • Use your environment’s planning mechanism (e.g., update_plan if available) to track phases and prevent drifting.
   • Prefer 4–7 steps; keep exactly one step in progress.

4. Decompose into subsystems

   • Choose subsystems that can be audited independently (API surface, core logic, error handling, perf, integrations, tests, docs).
   • For each subsystem, define 2–5 invariants (what must always be true).

5. Run dual independent audits per subsystem

   • Spawn two independent auditor agents per subsystem (auditA and auditB).
   • For high-risk or subtle work, narrow the subsystem scope and strengthen the invariants and evidence requirements before spawning them.
   • Tell them to work independently until reconciliation (no cross-talk).
   • Require evidence for every issue (repo location, deterministic repro, expected vs actual, severity).

6. Reconcile audits into a single confirmed issue list

   • Compare auditA vs auditB outputs and keep only mutually confirmed issues (or independently verify disputed ones with explorer).
   • Track rejected candidates with a brief reason (weak evidence, out of scope, non-deterministic).
   • Use this reconciled list as the only input to implementation.
   • Reconciliation output:
     • Confirmed issues (only mutual)
     • Rejected candidates (reason)
     • Consensus achieved: YES/NO

7. Implement in clusters with clear ownership

   • Group confirmed issues into clusters that can be fixed with minimal coupling.
   • Spawn exactly one implementer per cluster.
   • Assign each implementer a file set to “own” and require them to avoid broad refactors.
   • Do not implement any cluster work directly; always delegate to the implementer (even for “quick” changes).
   • Every fix must come with a regression test (unit/integration/e2e as appropriate).
   • For each cluster, run a two-stage review loop:
     • Have the implementer complete the cluster (tests, self-review) and report what changed.
     • spec_reviewer validates “nothing more, nothing less” by reading code (do not trust the report).
     • quality_reviewer validates maintainability and test quality (only after spec compliance passes).
     • If any review FAILs, send concrete feedback to the implementer and repeat the failed review stage.

8. Enforce review gates

   • Do not merge/land a cluster unless spec compliance PASS and code quality PASS are both recorded with concrete references.

9. Integrate + validate

   • Run the repo’s standard validations (tests, lint, build, typecheck).
   • If the repo has no clear commands, discover them from README, package.json, pyproject.toml, CI config, etc.

10. Deliver a concise completion report

    • State what is usable now.
    • State what remains intentionally unsupported (with next steps/issues).
    • List commands executed (at least key validation commands) and results.

What to send to sub-agents

Keep your messages task-specific and concise. Do not restate generic role behavior; focus on the task at hand.

For any audit/review/implementation message, include:

• Goal + success criteria (what “done” means)
• Scope boundaries / owned files (what to touch, what not to touch)
• Invariants (2–5) that must hold
• Commands to run (if known), and what evidence to collect