skill-diet

nicobailon/skill-diet is an agent skill that slims your other agent skills, then proves the slim version still works. It runs each task with the old skill, the new one and no skill at all, 3 times each, and keeps the cut only if the new one scores at least as well.

I ran it on three of my skills with gpt-6-luna:

• adr: SKILL.md went from 13 KB to 1.6 KB, 30/30 before and after. With no skill it still passed 26/30. The model already knew ADRs.
• notion: 32/33 to 33/33 at 55% fewer tokens per run. With no skill, the agent did one-line edits with a whole-page replace and reported success.
• web-browser: 16 KB to 6.4 KB. The no-skill runs used twice the tokens of the old skill, because the agent explored the scripts by hand.

The size cut was not the best part. For a skill that wraps a tool, it checks every claim against the tool and your session logs. It found 16 places where my skills or scripts were wrong, such as agent.mjs --domain x.com silently setting no allow-list. The rule I’m keeping: fix the tool’s error message before adding a line to the skill.

The cost: 1,434 agent sessions and 23.5M tokens for three skills, and a sandbox-exec profile, because the test agents kept finding my installed skills on disk.

The diet commit shows what got cut, and the full report covers the method and the costs.