SkillHone

Forgejo REST API toolkit — manage issues, pull requests, wikis, and repos on a Forgejo server. Use when the agent needs to file an issue, open / review / merge a PR, read or write a wiki page, or look up repo / branch info. One standalone script per resource type. Reads credentials from environment, `~/.skillhone/settings.json`, or `_data/forgejo_config.txt`.

SkillHone — toolkit for evaluating, optimizing, and managing agent skills. Use when asked to "evaluate a skill", "run probe", "optimize/iterate a skill", "create a new skill experiment", "seed a skill repo", or "run skill benchmarks"; also use when the user mentions a Forgejo-hosted skill repo and wants to measure or improve its quality. Wraps standalone scripts: status, eval, optim, new, seed, serve, synth.

Optimize a skill by planning, exploring available tools, diagnosing failures, and implementing fixes via PR. Use this skill as soon as an optimization loop starts, especially on the first iteration when community tools or reference approaches should be explored before implementation.

Use this skill to synthesize closed-form, automatically verifiable benchmark Q/A by exploring a tool environment, building a reusable exploration graph, and mining multiple hard questions from that graph. Use for: building a benchmark, writing eval items, generating evaluation data, closed-form QA, verifiable-answer datasets, synthesising eval data. Applies to any domain with callable tools. Do not use for open-ended writing, subjective scoring, or pure labeling.

Run and interpret skill evaluations. Use when you need to evaluate a skill, run probe/test/PR-val, check if a PR regresses quality, compare two versions, or diagnose why the score dropped. Handles the full eval lifecycle including solver trajectory diagnosis for tool-level error detection.

Interactively gather a PRD (Product Requirements Document) for an agent skill that is about to be built or optimized by SkillHone. Use when the user says things like "I want to write a new skill", "help me spec this skill", "what should <x>-skill do", or before running `skillhone new` / `skillhone optim` on a skill whose requirements aren't fully nailed down. The interview is driven through the `AskUserQuestion` tool — every round is a small set of dependent multi-choice questions, and the skill keeps asking until the user says stop. Final artifacts are three files in the paired `<skill>-eval` repo: `PRD.md` (eval-agent-visible), `PRD.improver_only.md` (improver-agent visible, scoring rubric redacted), and `PRD.choice.md` (the AskUserQuestion transcript). Also mirrors the appropriate pages into Forgejo wiki checkouts when available.