# Repo Visuals Retro > Retrospective meta-skill for the `repo-visuals` skill. Reads accumulated evaluation logs from past runs, spots patterns (recurring low-score criteria, repeated iteration failures, unsatisfied requests), consults other expert skills (skill-creator, frontend-design, etc.) where relevant, and proposes concrete edits to `repo-visuals/SKILL.md` as a reviewable diff. Runs on-demand, not per run. - **Type:** Skill - **Install:** `agentstack add skill-livlign-claude-skills-repo-visuals-retro` - **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior - **Seller:** [livlign](https://agentstack.voostack.com/s/livlign) - **Installs:** 0 - **Category:** [Agent Skills](https://agentstack.voostack.com/c/agent-skills) - **Latest version:** 0.1.0 - **License:** MIT - **Upstream author:** [livlign](https://github.com/livlign) - **Source:** https://github.com/livlign/claude-skills/tree/main/plugins/repo-visuals/skills/repo-visuals-retro ## Install ```sh agentstack add skill-livlign-claude-skills-repo-visuals-retro ``` Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent. ## About # 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 the stage was < 400 px tall — type legibility likely" - "3 runs had identical user feedback: 'loop seam is jarring'" ### 3. Consult expert skills For each pattern, consult the relevant expert skill(s) if available in the environment. Examples: - **Visual / design critique** → `frontend-design` skill. Feed it the final HTML + screenshots from low-scoring runs; ask for specific design-rule violations. - **Skill structure / prompt design** → `skill-creator` skill. Ask whether the skill's Phase N language is ambiguous or missing a step. - **Evaluation methodology** → any `evaluate-plugins` style skill. Ask whether the 5-criterion scorecard is well-calibrated. - **Domain-specific knowledge** → e.g. an ast-graph / codebase-compare skill if patterns suggest weaknesses in the scan phase. Detect which skills are actually available — don't reference non-existent ones. ### 4. Propose edits Write a diff-style proposal: for each pattern, which section of the `repo-visuals` skill's `SKILL.md` changes and why. Example: ``` Pattern: Hero moment delivery weak on CLI tools (2.6/5 avg over 4 runs). Hypothesis: §1.4a probes don't surface CLI-specific hero moments (install speed, clear command output, shell ergonomics). Proposed edit to §1.4a: add a CLI-tool branch to the probing list with 3 tool-specific prompts. ``` Show the proposed diff. Wait for user approval before applying. ### 5. Apply & update aggregate On user approval: - Edit the `repo-visuals` skill's `SKILL.md` with the approved changes - Append a retro summary to `./evaluations/index.md` (date, patterns identified, edits applied) - Move the raw run files that informed this retro into `./evaluations/runs/processed/` so the next retro only sees new samples ## Outputs - Updated `repo-visuals` skill `SKILL.md` - Updated `./evaluations/index.md` with retro summary - Moved processed run files ## What this skill does NOT do - Does not run `repo-visuals` itself - Does not auto-apply edits without user approval - Does not invent criteria — it only improves the skill against its existing scorecard ## Source & license This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code. - **Author:** [livlign](https://github.com/livlign) - **Source:** [livlign/claude-skills](https://github.com/livlign/claude-skills) - **License:** MIT Install and usage instructions live in the source repository linked above. ## Pricing - **Free** — Free ## Security capabilities Automated source analysis of v0.1.0 — what this tool can access: - **Network access:** no - **Filesystem access:** no - **Shell / process execution:** no - **Environment & secrets:** no - **Dynamic code execution:** no *"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.* ## Versions - **0.1.0** — security scan: passed — Imported from the upstream source. ## Links - Listing page: https://agentstack.voostack.com/l/skill-livlign-claude-skills-repo-visuals-retro - Seller: https://agentstack.voostack.com/s/livlign - Browse the marketplace: https://agentstack.voostack.com/browse --- Listed on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.