experiment-craft

experiment-craft is a Model training & evaluation skill for AI agents, published by EvoScientist in the EvoSkills repository on GitHub. Skillspace rates experiment-craft C (70/100) and it passed the safety scan; the rating is based on static analysis only.

Use this skill when the user wants to debug, diagnose, or systematically iterate on an experiment that already exists, or when they need a structured experiment log for tracking runs, hypotheses, failures, results, and next steps during active research. Apply it to underperforming methods, training that will not converge, regressions after a change, inconsistent results across datasets, aimless experimentation without progress, and questions like 'why doesn't this work?', 'no progress after many attempts', or 'how should I investigate this failure?'. Also use it for setting up practical experiment logging/record-keeping that supports debugging and iteration. Do not use it for designing a brand-new experiment pipeline or full experiment program (use experiment-pipeline), generating research ideas, fixing isolated coding/syntax errors, or writing retrospective summaries into research memory/notes/knowledge bases.

Grade

C

Quality

70 / 100

Safety

Passed

GitHub stars

411

Unproven: rated by static analysis only, not yet compared head-to-head.

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