format-answer

Toy skill used by the hello-harbor example. Teaches an agent to answer a question by writing the value, wrapped in <answer></answer> tags, to the file the task names.

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Repository: kernel/pi-skillopt
Last source activity: June 5, 2026 at 21:48
Detected SKILL.md language: English
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Forks: 0

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manual-testing

Playbook for running a manual, end-to-end test of the pi-skillopt plugin in a real pi session — drive the skillopt-create / taskpack / finalize skills against an example, watch the loop progress, and analyze the run. Use when asked to "manually test skillopt", "smoke-test the plugin", "run a skillopt session and see how it goes", or to reproduce/verify a reported skillopt behavior. Repo-local dev tooling — not shipped to plugin users.

2026-06-08

skillopt-create

Set up and run a SkillOpt-style optimization loop for a single agent SKILL.md, scored by Harbor rollouts. Gathers the skill, the rollout environment (backend, agent, model, preloads), generates a task pack if none exists, then starts the loop. Use when asked to "optimize this skill", "skillopt this SKILL.md", "train my skill", or "improve my agent skill against evals".

2026-06-08

skillopt-finalize

Close out a skillopt run — measure the optimized skill on the held-out test split, produce best_skill.md, and emit a clean diff + report against the original skill. Use when a skillopt loop has plateaued or the user asks to "finalize", "wrap up the skillopt run", or "get the final number".

2026-06-08

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format-answer

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format-answer

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format-answer

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name	format-answer
description	Toy skill used by the hello-harbor example. Teaches an agent to answer a question by writing the value, wrapped in <answer></answer> tags, to the file the task names.

format-answer

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format-answer

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format-answer

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