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BAIME-aligned refactoring protocol for Go hotspots (CLIs, services, MCP tooling) with automated metrics (e.g., metrics-cli, metrics-mcp) and documentation.
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Baseado na classificação ocupacional SOC
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Track and optimize agent specialization during methodology development. Use when agent specialization emerges (generic agents show >5x performance gap), multi-experiment comparison needed, or methodology transferability analysis required. Captures agent set evolution (Aₙ tracking), meta-agent evolution (Mₙ tracking), specialization decisions (when/why to create specialized agents), and reusability assessment (universal vs domain-specific vs task-specific). Enables systematic cross-experiment learning and optimized M₀ evolution. 2-3 hours overhead per experiment.
Routes tasks to appropriate Task tool agents (subagents). Triggers on complex multi-step tasks, research, code review, exploration, or any task benefiting from specialized agent execution. Matches intent to agent types.
| name | Code Refactoring |
| description | BAIME-aligned refactoring protocol for Go hotspots (CLIs, services, MCP tooling) with automated metrics (e.g., metrics-cli, metrics-mcp) and documentation. |
| allowed-tools | Read, Write, Edit, Bash, Grep, Glob |
λ(target_pkg, target_hotspot, metrics_target) → (refactor_plan, metrics_snapshot, validation_report) | ∧ configs = read_json(experiment-config.json)? ∧ catalogue = configs.metrics_targets ∨ [] ∧ require(cyclomatic(target_hotspot) > 8) ∧ require(catalogue = [] ∨ metrics_target ∈ catalogue) ∧ require(run("make " + metrics_target)) ∧ baseline = results.md ∧ iterations/ ∧ apply(pattern_set = reference/patterns.md) ∧ use(templates/{iteration-template.md,refactoring-safety-checklist.md,tdd-refactoring-workflow.md,incremental-commit-protocol.md}) ∧ automate(metrics_snapshot) via scripts/{capture-*-metrics.sh,count-artifacts.sh} ∧ document(knowledge) → knowledge/{patterns,principles,best-practices} ∧ ensure(complexity_delta(target_hotspot) ≥ 0.30 ∧ cyclomatic(target_hotspot) ≤ 10) ∧ ensure(coverage_delta(target_pkg) ≥ 0.01 ∨ coverage(target_pkg) ≥ 0.70) ∧ validation_report = validate-skill.sh → {inventory.json, V_instance ≥ 0.85}
