Recommend Evolution

Overview

Recommend ecosystem evolution when repeated evidence indicates missing capability, and record the recommendation in a standard machine-readable format.

When to Use

• Reflection identifies recurring delivery failures with the same root cause

• Router/analysis signals no suitable agent or skill for recurring requests

• Repeated integration gaps imply missing artifact type or policy

• User explicitly requests a new capability path

Iron Laws

• NEVER spawn evolution-orchestrator directly from this skill — this skill records recommendations only; execution decisions belong to the orchestrator and approval pipeline.

• ALWAYS validate trigger type against defined thresholds before recording a recommendation — vague observations are not triggers; require concrete failure counts or routing misses.

• NEVER create a new evolution request when artifact-integrator or skill-updater would address the gap — reserve evolution for net-new capabilities, not integration or update gaps.

• ALWAYS append the recommendation to the JSONL queue AND include the required report block in the current output — dual recording ensures the recommendation is discoverable at both runtime and review time.

• NEVER proceed with a recommendation without evidence — single failures are noise; trigger thresholds exist for a reason.

Trigger Taxonomy Note

recommend-evolution uses a cause-oriented trigger taxonomy (repeated_error , no_agent , integration_gap , user_request , rubric_regression , stale_skill , other ).

This intentionally differs from skill-updater , which uses a caller-oriented trigger taxonomy (reflection , evolve , manual , stale_skill ) to describe who/what initiated the update path.

Step 0: Validate Trigger Type

Use these thresholds:

• repeated_error : same class of failure in 5+ tasks

• rubric_regression : repeated score drop below threshold for same class of task

• no_agent : recurring need with no valid routing match

• integration_gap : existing artifact integration missing (prefer artifact-integrator)

• user_request : explicit request for capability not available

• stale_skill : audit pipeline reports verified artifact older than 6 months or invalid lastVerifiedAt

Step 1: Decide Recommendation Path

• If gap is integration of existing artifact, prefer: Skill({ skill: 'artifact-integrator' })

• If gap is stale/underperforming existing skill, prefer: Skill({ skill: 'skill-updater' })

• If gap requires net-new capability/artifact, continue with evolution recommendation

• If no artifact change needed, update memory only and exit

Step 2: Create Standard Recommendation Payload

Build one JSON object with required fields:

{ "timestamp": "2026-02-14T00:00:00.000Z", "source": "reflection-agent", "trigger": "repeated_error", "evidence": "Same routing failure observed in 6 tasks over 2 days.", "suggestedArtifactType": "skill", "summary": "Create a new routing-context skill for reflection-time grounding.", "status": "proposed" }

Schema reference: .claude/schemas/evolution-request.schema.json

Step 3: Record Recommendation

• Append JSON line to: .claude/context/runtime/evolution-requests.jsonl

• Add required report block:

Evolution Recommendation

• Trigger: <trigger>
• Evidence: <evidence>
• Suggested Artifact Type: <type|null>
• Summary: <1-2 sentences>
• Queue Record: .claude/context/runtime/evolution-requests.jsonl

Step 3: Output

Return recommendation summary and what was recorded.

</execution_process>

// Repeated failure pattern -> recommend skill creation Skill({ skill: 'recommend-evolution', args: '--trigger repeated_error --suggestedArtifactType skill', });

// Routing miss -> recommend new agent/workflow discussion Skill({ skill: 'recommend-evolution', args: '--trigger no_agent --suggestedArtifactType agent' });

</usage_example>

Anti-Patterns

Anti-Pattern Why It Fails Correct Approach

Spawning evolution-orchestrator directly from this skill Violates single-responsibility; bypasses approval and resource gates Record recommendation to JSONL queue only; let the orchestrator decide on execution

Recording an evolution request for an integration gap that already has artifacts Creates unnecessary new artifacts when an integration fix would suffice Check artifact-integrator path first; escalate only if gap requires net-new capability

Submitting a recommendation without trigger evidence Uninformed evolution wastes resources and pollutes the queue with noise Require concrete evidence: failure counts, routing miss logs, or explicit user request

Routing stale-skill triggers through this skill instead of skill-updater Wrong escalation path; creates evolution requests for work that belongs in an update cycle Route stale_skill triggers directly to skill-updater; only escalate if the skill cannot be updated

Triggering evolution after a single failure instance Single failures are noise; premature evolution wastes build capacity Apply defined thresholds: 5+ repeated errors, consistent routing misses across sessions

Memory Protocol (MANDATORY)

Before starting:

Read .claude/context/memory/learnings.md using Read or Node fs.readFileSync (cross-platform).

After completing:

• Recommendation pattern -> .claude/context/memory/learnings.md

• Ambiguous trigger logic -> .claude/context/memory/issues.md

• Evolution policy decision -> .claude/context/memory/decisions.md

ASSUME INTERRUPTION: Your context may reset. If it's not in memory, it didn't happen.