# Recursive Improvement > Recursive Improvement - Skill: `dnyoussef/recursive-improvement` (Agent Skill, multi-file: 2 files) - Install (CLI): `npx skillmds@latest add dnyoussef/recursive-improvement` - Raw SKILL.md: https://api.skillmd.com/api/skills/dnyoussef/recursive-improvement/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Coding & Dev Tools - Author: DNYoussef (https://skillmd.com/u/dnyoussef) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/dnyoussef/recursive-improvement --- /*============================================================================*/ /* SKILL SKILL :: VERILINGUA x VERIX EDITION */ /*============================================================================*/ --- name: SKILL version: 1.0.0 description: | [assert|neutral] SKILL skill for foundry workflows [ground:given] [conf:0.95] [state:confirmed] category: foundry tags: - general author: system cognitive_frame: primary: compositional goal_analysis: first_order: "Execute SKILL workflow" second_order: "Ensure quality and consistency" third_order: "Enable systematic foundry processes" --- /*----------------------------------------------------------------------------*/ /* S0 META-IDENTITY */ /*----------------------------------------------------------------------------*/ [define|neutral] SKILL := { name: "SKILL", category: "foundry", version: "1.0.0", layer: L1 } [ground:given] [conf:1.0] [state:confirmed] /*----------------------------------------------------------------------------*/ /* S1 COGNITIVE FRAME */ /*----------------------------------------------------------------------------*/ [define|neutral] COGNITIVE_FRAME := { frame: "Compositional", source: "German", force: "Build from primitives?" } [ground:cognitive-science] [conf:0.92] [state:confirmed] ## Kanitsal Cerceve (Evidential Frame Activation) Kaynak dogrulama modu etkin. /*----------------------------------------------------------------------------*/ /* S2 TRIGGER CONDITIONS */ /*----------------------------------------------------------------------------*/ [define|neutral] TRIGGER_POSITIVE := { keywords: ["SKILL", "foundry", "workflow"], context: "user needs SKILL capability" } [ground:given] [conf:1.0] [state:confirmed] /*----------------------------------------------------------------------------*/ /* S3 CORE CONTENT */ /*----------------------------------------------------------------------------*/ # Recursive Improvement - Meta-Loop Skill ## Kanitsal Cerceve (Evidential Frame Activation) Kaynak dogrulama modu etkin. --- name: recursive-improvement description: Self-improving meta-loop that audits and enhances skills, prompts, and expertise files category: foundry version: 2.0.0 triggers: - "improve skill" - "audit skill" - "run improvement cycle" - "meta-loop" - "self-improve" mcp_servers: required: [memory-mcp] optional: [connascence-analyzer] --- ## Trigger Keywords **USE WHEN user mentions:** - "improve skill", "audit skill", "enhance skill", "optimize skill" - "run improvement cycle", "meta-loop", "self-improve" - "skill quality check", "documentation audit" - "recursive improvement", "systematic improvement" - "batch improve skills", "improve all skills" - "skill missing [section]", "incomplete documentation" **DO NOT USE when:** - User wants to CREATE a new skill - use skill-creator-agent or micro-skill-creator - User wants to CREATE an agent - use agent-creator - User wants to improve a PROMPT (not skill) - use prompt-architect - User wants one-off manual fix - direct editing faster - Eval-harness benchmarks failing - fix root cause first, not improve on broken baseline - During active feature development - finish feature, then improve **Instead use:** - skill-creator-agent when creating new skills from scratch - agent-creator when creating new agents - prompt-architect when optimizing prompts - skill-forge when applying specific improvements (recursive-improvement coordinates it) ## Overview The Recursive Improvement skill orchestrates the meta-loop that enables the system to improve itself. It coordinates four specialized auditors (skill-auditor, prompt-auditor, expertise-auditor, output-auditor) to detect issues, generate improvement proposals, apply changes via skill-forge, and validate results through the frozen eval-harness. **Key Constraint**: The eval-harness is FROZEN - it never self-improves. This prevents Goodhart's Law (optimizing the metric instead of the goal). ## When to Use **Use When**: - Skill documentation is incomplete (missing Core Principles, Anti-Patterns, Conclusion) - Prompt quality has degraded (inconsistent outputs, missing constraints) - Expertise files are outdated (file locations changed, patterns stale) - Output quality has dropped (theater code, unvalidated claims) **Do Not Use**: - For one-off fixes (use direct editing) - When eval-harness benchmarks are failing (fix root cause first) - During active feature development (finish feature first) ## Core Principles Recursive Improvement operates on 3 fundamental principles: ### Principle 1: Frozen Eval Harness Prevents Goodhart's Law The evaluation harness that gates all improvements is NEVER self-improved. This ensures the system optimizes for genuine quality, not for passing corrupted benchmarks. In practice: - Eval-harness benchmarks are defined externally and versioned separately - Changes to eval-harness require human approval and audit trail - All improvement proposals are tested against frozen benchmarks before commit ### Principle 2: Propose-Test-Compare-Commit Pipeline Every improvement follows a rigorous pipeline: propose changes, test against benchmarks, compare to baseline, commit only if better. No direct edits bypass this pipeline. In practice: - Auditors generate structured proposals with predicted improvement deltas - skill-forge applies proposals in sandbox before production - A/B comparison ensures new version outperforms baseline - Rollback available for 30 days if regressions discovered later ### Principle 3: Documentation Completeness Is Non-Negotiable Skills are not production-ready until they pass documentation audit (100% Tier 1, 100% Tier 2). Missing sections are auto-generated using templates from SKILL-AUDIT-PROTOCOL.md. In practice: - Every skill audit checks for Core Principles, Anti-Patterns, Conclusion - Missing sections trigger auto-generation using domain-specific t /*----------------------------------------------------------------------------*/ /* S4 SUCCESS CRITERIA */ /*----------------------------------------------------------------------------*/ [define|neutral] SUCCESS_CRITERIA := { primary: "Skill execution completes successfully", quality: "Output meets quality thresholds", verification: "Results validated against requirements" } [ground:given] [conf:1.0] [state:confirmed] /*----------------------------------------------------------------------------*/ /* S5 MCP INTEGRATION */ /*----------------------------------------------------------------------------*/ [define|neutral] MCP_INTEGRATION := { memory_mcp: "Store execution results and patterns", tools: ["mcp__memory-mcp__memory_store", "mcp__memory-mcp__vector_search"] } [ground:witnessed:mcp-config] [conf:0.95] [state:confirmed] /*----------------------------------------------------------------------------*/ /* S6 MEMORY NAMESPACE */ /*----------------------------------------------------------------------------*/ [define|neutral] MEMORY_NAMESPACE := { pattern: "skills/foundry/SKILL/{project}/{timestamp}", store: ["executions", "decisions", "patterns"], retrieve: ["similar_tasks", "proven_patterns"] } [ground:system-policy] [conf:1.0] [state:confirmed] [define|neutral] MEMORY_TAGGING := { WHO: "SKILL-{session_id}", WHEN: "ISO8601_timestamp", PROJECT: "{project_name}", WHY: "skill-execution" } [ground:system-policy] [conf:1.0] [state:confirmed] /*----------------------------------------------------------------------------*/ /* S7 SKILL COMPLETION VERIFICATION */ /*----------------------------------------------------------------------------*/ [direct|emphatic] COMPLETION_CHECKLIST := { agent_spawning: "Spawn agents via Task()", registry_validation: "Use registry agents only", todowrite_called: "Track progress with TodoWrite", work_delegation: "Delegate to specialized agents" } [ground:system-policy] [conf:1.0] [state:confirmed] /*----------------------------------------------------------------------------*/ /* S8 ABSOLUTE RULES */ /*----------------------------------------------------------------------------*/ [direct|emphatic] RULE_NO_UNICODE := forall(output): NOT(unicode_outside_ascii) [ground:windows-compatibility] [conf:1.0] [state:confirmed] [direct|emphatic] RULE_EVIDENCE := forall(claim): has(ground) AND has(confidence) [ground:verix-spec] [conf:1.0] [state:confirmed] [direct|emphatic] RULE_REGISTRY := forall(agent): agent IN AGENT_REGISTRY [ground:system-policy] [conf:1.0] [state:confirmed] /*----------------------------------------------------------------------------*/ /* PROMISE */ /*----------------------------------------------------------------------------*/ [commit|confident] SKILL_VERILINGUA_VERIX_COMPLIANT [ground:self-validation] [conf:0.99] [state:confirmed]