{"slug":"telagod-ml","source_name":"telagod/ml","name":"Telagod/ML","description":"Machine learning and LLM engineering judgment, distilled from a stronger model - invoke when DECIDING whether/how to use ML or an LLM for a task (prompt vs RAG vs fine-tune vs classical); working with training/eval data or labels; building or reviewing evals for models and LLM features; designing RAG, structured output, or agent pipelines; or diagnosing why a model/LLM feature underperforms. Method-selection ladder, data and leakage discipline, eval-as-spec rules, LLM-era craft, and a trap catal","version":1,"lift":{"pass_rate_delta_pts":4.55,"pass_rate_pct":100,"total_cases":22,"passed_cases":22,"tokens_delta_pct":5.2,"turns_delta_pct":0,"verdict":"pass","benchmark_model":"gemini-3.6-flash","grading_method":"judged","completed_at":"2026-08-24T19:29:45.944431+00:00"},"skill_score":1,"benchmark_models":[{"model":"gemini-3.6-flash","headline":true,"delta_pts":4.55,"with_pass_pct":100,"without_pass_pct":95.5,"tokens_delta_pct":5.2,"turns_delta_pct":0,"total_cases":22,"cases_aggregated":22,"verdict":"pass","never_hurt":true,"completed_at":"2026-08-24T19:29:45.944431+00:00","run_id":"a6cde7f4-0335-4131-a55b-a741f204430a","version_number":1,"is_latest_version":true,"gate":null}],"trust":{"skill_safety":"passed","safety_status":"clean","intent_verdict":"safe","content_status":"clean","indexable":true},"license":"MIT","install_count":0,"manifest_hash":"823f0a7233d8a28d0f5e3492e56ddc2901f522846188cfee36f743b0da9760c3","raw_url":"https://app.decimal.ai/s/telagod-ml/SKILL.md","scorecard_url":"https://app.decimal.ai/skills/telagod-ml"}