Ruflo v3.32.35: Adaptive Swarms and Safer Learning Loops

Ruflo v3.32.35 gives long-running agent teams a controlled way to learn which workers should receive future tasks. The new pheromone-adaptive topology combines outcome, latency, and consensus signals while preserving protected roles, a minimum active quorum, and existing permissions. It begins in dry-run mode so teams can inspect its decisions before enabling scheduling changes.

This release also makes the surrounding learning loop more trustworthy: project flywheels must evaluate against a project-local, hash-pinned benchmark; learned routing updates inside a live MCP process; AgentDB deletes and upserts remove stale vectors; and daemon auto-start is limited to actual Ruflo projects.

Install or upgrade

npm install --global [email protected]
ruflo doctor

Existing installations remain compatible. The default topology is still hierarchical, old swarm state remains readable, historical flywheel receipts remain verifiable, and the new adaptive scheduler is opt-in.

Try adaptive swarm scheduling

Start in the default calibration mode:

ruflo swarm init \
  --topology pheromone-adaptive \
  --max-agents 8

ruflo swarm pheromone
ruflo agent metrics --format json

When the observations look right, explicitly enable scheduling enforcement:

ruflo swarm init \
  --topology pheromone-adaptive \
  --max-agents 8 \
  --apsc-live

Live mode changes Ruflo dispatch eligibility only. It does not terminate agents, revoke access, discard context, or widen permissions.

Use a project-local flywheel anchor

Create .claude/eval/flywheel-anchor.manifest.json:

{
  "schemaVersion": "ruflo.flywheel-anchor-manifest/v1",
  "path": "my-project-anchor.json",
  "sha256": "sha256:<canonical-task-hash>"
}

The referenced anchor contains at least four labelled tasks. Ruflo binds its canonical hash into new evaluation receipts. A non-Ruflo repository without a project anchor now fails closed instead of silently optimizing against Ruflo's built-in development benchmark.

What changed

• Adds the opt-in pheromone-adaptive swarm topology with role-aware EMA scoring, dry-run calibration, protected roles, quorum floors, bounded exploration, atomic cross-process updates, CLI inspection, and MCP tools.
• Connects hooks post-task outcomes to adaptive scheduling and exposes each agent's score, sample count, role, and eligibility through agent metrics.
• Adds hash-pinned, project-local flywheel evaluation anchors and receipt binding while retaining historical receipt verification.
• Makes learned routing use supported, discriminative evidence and immediately invalidates a warm router after labelled outcomes.
• Makes AgentDB logical-key upserts, deletes, and cleanup reconcile every stale vector and report accurate lifecycle metrics.
• Limits daemon auto-start to projects containing .claude-flow/, reports the first start, and applies a 30-minute abandoned-daemon idle timeout.

Measured benchmark

On the declared synthetic benchmark (12 agents, 20,000 updates), adaptive scheduling produced:

• 33.3% active-agent reduction;
• +0.2617 admitted mean score;
• 0.0066 ms update p95 in the release validation run;
• preserved quorum and protected-role invariants.

These are Ruflo benchmark results for that workload, not a universal production performance claim.

Validation

• TypeScript builds passed for @claude-flow/shared, @claude-flow/swarm, and @claude-flow/cli.
• The changed-surface suite passed 93 tests across nine files.
• Twenty concurrent outcome writers persisted all twenty rounds with no residual lock.
• Built CLI smoke tests covered initialization, automatic post-task learning, status, manual updates, and JSON metrics.
• CI/CD, V3 CI/CD, CodeQL, cross-agent integration, CVE audit, and verification workflows passed on the merged commit.

This release ships #2848 and resolves #2815, #2819, #2832, #2834, #2839, and #2840.