diegosouzapw Cross-Evolution
Purpose
Maintain a high evolutionary standard across all agent skills by identifying "Genes" (best practices), transferring them to skills that lack these features, and discovering new high-value genes from existing skills.
Axioms
1. Atomic Independence (No Cross-Skill Glue)
Skills and their scripts must be 'atomic'.
- 'FORBIDDEN': Any logic inside a skill's script that explicitly checks for or calls tools from another skill.
- 'The Agent is the Glue': Only the AI Agent is responsible for coordination.
2. Pragmatic Evolution (Occam's Razor)
- 'Just-In-Time Transfer': A gene is transferred only when it solves a recurring problem.
- 'KISS Compliance': Avoid bloating skills with genes they don't need.
- 'Fitness-Driven': Prioritize genes with highest weight for maximum fitness gain.
3. Living Protocol
This skill proactively evolves itself and its gene registry upon discovering new constraints.
Core Concepts
Gene
A modular implementation or documentation pattern that improves skill quality.
Genes have a 'lifecycle': Proposed → Active → Deprecated → Extinct.
Full registry with weights, detection rules, and conflicts: docs/genes.md
Horizontal Gene Transfer (HGT)
Copying a gene from a donor skill to a recipient without rewriting the recipient's core purpose.
Gene Discovery
Scanning existing skills for repeated high-value patterns not yet represented in the registry.
If a candidate passes thresholds, it is automatically written into docs/genes.md under "Proposed Genes".
Genetic Drift
Genes carried by zero skills are candidates for deprecation. After sustained non-adoption, they go extinct.
Fitness
Quantitative health score per skill: earned_weight / applicable_weight × 100%.
Domain-specific genes (recommend=none) only count if already present — reward, not penalty.
Recombination
When two genes conflict in the same skill, selective pressure creates a new hybrid gene.
Operating Modes
Mode 1: Scan & Audit
'Automated': bash "${SKILL_DIR}/scripts/audit-genes"
Produces: Gene × Skill matrix, fitness scores, genetic drift warnings, conflict alerts, recommendations, and discovered gene candidates (with registry sync).
Useful flags:
--no-discovery— skip discovery phase.--no-sync-discovery— discover candidates without writing to registry.
Mode 2: Mutation (Update)
Inject missing/extra genes into a target skill. Prioritize by weight × fitness impact.
'Value guard': Before transferring a gene, ask: "Does this gene solve a real problem the skill has encountered, or are we just making the fitness number go up?" If the latter — skip the transfer. Fitness score is a heuristic, not a goal. Optimizing the score instead of skill quality is the Farmville trap.
Mode 3: Speciation (Creation)
Create a new gene/skill by combining existing patterns (triggered by gene conflicts or recombination).