repo-visuals-retro

# repo-visuals-retro The `repo-visuals` skill scores every run on five criteria (see `repo-visuals/SKILL.md` §6). This meta-skill turns that accumulated evidence into skill improvements. ## When to invoke - You have ≥ 5 runs logged in `./evaluations/runs/` in the user's working directory (before that, the sample is noise). - Something feels off across multiple runs and you want a structured look. - A major change to `repo-visuals` is planned and you want the evidence base first. Do **not** run this every session. Retros are more valuable with accumulated samples. ## Inputs - The `repo-visuals` skill's `SKILL.md` — the current skill definition (sibling skill in the same plugin) - `./evaluations/index.md` in the user's working directory — curated aggregate from previous retros - `./evaluations/runs/*.md` in the user's working directory — all per-run raw evaluations since the last retro - Available expert skills in the environment (detected, not assumed) ## Workflow ### 1. Read & tabulate Read all inputs. Build a small table: - Average score per criterion, overall and by repo-type bucket (CLI, library, web-app, etc. — infer from scan metadata in each run) - Variance per criterion (high variance = the skill is inconsistent on that axis) - Free-text feedback clustered by theme ### 2. Identify patterns Name each pattern concretely: - "Hero moment delivery averaged 2.6 / 5 across the 4 CLI-tool runs but 4.2 / 5 across library runs" - "Technical polish dropped whenever t...