{"id":"f730e9a2-f088-4954-8311-6c4aaf02e06c","slug":"clawhub-skills-aaronjmars-iterative-code-evolution","name":"iterative-code-evolution","description":"Systematically improve code through structured analysis-mutation-evaluation loops. Adapted from ALMA (Automated meta-Learning of Memory designs for Agentic systems). Use when iterating on code quality, optimizing implementations, debugging persistent issues, or evolving a design through multiple improvement cycles. Replaces ad-hoc \"try and fix\" with disciplined reflection, variant tracking, and principled selection of what to change next.","canonicalUrl":"https://www.xpersona.co/agent/clawhub-skills-aaronjmars-iterative-code-evolution","sourceUrl":"https://github.com/openclaw/skills/tree/main/skills/aaronjmars/iterative-code-evolution","homepage":null,"source":"CLAWHUB","vendor":{"slug":"openclaw","label":"Openclaw","url":"https://github.com/openclaw/skills/tree/main/skills/aaronjmars/iterative-code-evolution"},"protocols":["OPENCLEW"],"capabilities":[],"trustScore":null,"trustConfidence":"unknown","artifactCount":0,"benchmarkCount":0,"lastRelease":null,"freshnessAt":"2026-02-25T05:54:46.570Z","freshnessLabel":"Feb 25, 2026","securityReviewed":true,"openapiReady":false,"stats":[{"label":"Trust score","value":"Unknown"},{"label":"Compatibility","value":"OpenClaw"},{"label":"Freshness","value":"Feb 25, 2026"},{"label":"Vendor","value":"Openclaw"},{"label":"Artifacts","value":"0"},{"label":"Benchmarks","value":"0"},{"label":"Last release","value":"Unpublished"}],"factsPreview":[{"factKey":"docs_crawl","category":"integration","label":"Crawlable docs","value":"6 indexed pages on the official domain","href":"https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar","sourceUrl":"https://github.com/login?return_to=https%3A%2F%2Fgithub.com%2Fopenclaw%2Fskills%2Ftree%2Fmain%2Fskills%2Fasleep123%2Fcaldav-calendar","sourceType":"search_document","confidence":"medium","observedAt":"2026-04-15T05:03:46.393Z","isPublic":true},{"factKey":"vendor","category":"vendor","label":"Vendor","value":"Openclaw","href":"https://github.com/openclaw/skills/tree/main/skills/aaronjmars/iterative-code-evolution","sourceUrl":"https://github.com/openclaw/skills/tree/main/skills/aaronjmars/iterative-code-evolution","sourceType":"profile","confidence":"medium","observedAt":"2026-04-15T00:45:39.800Z","isPublic":true},{"factKey":"protocols","category":"compatibility","label":"Protocol compatibility","value":"OpenClaw","href":"https://www.xpersona.co/api/v1/agents/clawhub-skills-aaronjmars-iterative-code-evolution/contract","sourceUrl":"https://www.xpersona.co/api/v1/agents/clawhub-skills-aaronjmars-iterative-code-evolution/contract","sourceType":"contract","confidence":"medium","observedAt":"2026-04-15T00:45:39.800Z","isPublic":true},{"factKey":"handshake_status","category":"security","label":"Handshake status","value":"UNKNOWN","href":"https://www.xpersona.co/api/v1/agents/clawhub-skills-aaronjmars-iterative-code-evolution/trust","sourceUrl":"https://www.xpersona.co/api/v1/agents/clawhub-skills-aaronjmars-iterative-code-evolution/trust","sourceType":"trust","confidence":"medium","observedAt":null,"isPublic":true}],"highlights":["Trust evidence available"],"agentCard":{"name":"iterative-code-evolution","description":"Systematically improve code through structured analysis-mutation-evaluation loops. Adapted from ALMA (Automated meta-Learning of Memory designs for Agentic systems). Use when iterating on code quality, optimizing implementations, debugging persistent issues, or evolving a design through multiple improvement cycles. Replaces ad-hoc \"try and fix\" with disciplined reflection, variant tracking, and principled selection of what to change next.","source":"CLAWHUB","sourceId":"clawhub:skills:aaronjmars:iterative-code-evolution","repository":"https://github.com/openclaw/skills/tree/main/skills/aaronjmars/iterative-code-evolution","documentation":"https://www.xpersona.co/agent/clawhub-skills-aaronjmars-iterative-code-evolution","protocols":["OPENCLEW"],"languages":["typescript"],"examples":[{"kind":"example","language":"text","snippet":"┌─────────────────────────────────────────────────────┐\n│  1. ANALYZE  — structured diagnosis of current code │\n│  2. PLAN     — prioritized, concrete changes        │\n│  3. MUTATE   — implement the changes                │\n│  4. VERIFY   — run it, check for errors             │\n│  5. SCORE    — measure improvement vs. baseline     │\n│  6. ARCHIVE  — log what was tried and what happened │\n│                                                     │\n│  Loop back to 1 with new knowledge                  │\n└─────────────────────────────────────────────────────┘"},{"kind":"example","language":"json","snippet":"{\n  \"baseline\": {\n    \"description\": \"Initial implementation before evolution began\",\n    \"score\": 0.0,\n    \"timestamp\": \"2025-01-15T10:00:00Z\"\n  },\n  \"variants\": {\n    \"v001\": {\n      \"parent\": \"baseline\",\n      \"description\": \"Added input validation and error handling\",\n      \"changes_made\": [\n        {\n          \"what\": \"Added type checks on all public methods\",\n          \"why\": \"Runtime crashes from malformed input in 3/10 test cases\",\n          \"priority\": \"High\"\n        }\n      ],\n      \"score\": 0.6,\n      \"delta\": \"+0.6 vs parent\",\n      \"timestamp\": \"2025-01-15T10:30:00Z\",\n      \"learned\": \"Input validation was the primary failure mode — most other logic was sound\"\n    },\n    \"v002\": {\n      \"parent\": \"v001\",\n      \"description\": \"Refactored parsing logic to handle edge cases\",\n      \"changes_made\": [\n        {\n          \"what\": \"Rewrote parse_input() to use state machine instead of regex\",\n          \"why\": \"Regex approach failed on nested structures (seen in test cases 7,8)\",\n          \"priority\": \"High\"\n        }\n      ],\n      \"score\": 0.85,\n      \"delta\": \"+0.25 vs parent\",\n      \"timestamp\": \"2025-01-15T11:00:00Z\",\n      \"learned\": \"State machine approach generalizes better than regex for this grammar\"\n    }\n  },\n  \"principles_learned\": [\n    \"Input validation fixes give the biggest early gains\",\n    \"Regex-based parsing breaks on recursive structures — prefer state machines\",\n    \"Small targeted changes score better than large rewrites\"\n  ]\n}"}]}}