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AI & LLM Engineering · By seb1n
Skills
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| # | Skill | Repository | Stars | Used in | Tokens | Auto-check | Licence | Updated |
|---|---|---|---|---|---|---|---|---|
| 1 | Design and validate model-facing tool definitions with clear names, action-oriented descriptions, bounded JSON Schema parameters, explicit side effects, safe defaults, idempotency, errors, and… | seb1n/ | 206 | — | ~1.5k | Automated safety check: Pass | MIT | 2 mo ago |
| 2 | Optimize a complete candidate context package by deduplicating, filtering, ordering, and allocating its token budget. | seb1n/ | 206 | — | ~2.9k | Automated safety check: Pass | MIT | 2 mo ago |
| 3 | Rank an existing set of context chunks by relevance, diversity, freshness, and utility. | seb1n/ | 206 | — | ~2.9k | Automated safety check: Pass | MIT | 2 mo ago |
| 4 | Retrieve relevant information from a knowledge base using semantic, keyword, or hybrid search to ground a query. | seb1n/ | 206 | — | ~2.1k | Automated safety check: Pass | MIT | 2 mo ago |
| 5 | Train machine learning models end-to-end, covering data loading, preprocessing, architecture selection, training loops, validation, and checkpointing. | seb1n/ | 206 | — | ~2.4k | Automated safety check: Pass | MIT | 2 mo ago |
| 6 | Compress selected context to a target token budget while preserving decisions, evidence, constraints, and unresolved questions. | seb1n/ | 206 | — | ~2.2k | Automated safety check: Pass | MIT | 2 mo ago |