loop-check

Loop Check

Answer one question: "What's needed to make feedback loops autonomous in this repo?"

Find what's manual, what's missing, and prescribe concrete automation paths. This is not a full audit — it's a focused scan on feedback loops only.

Process

1. Discover workflows
2. Assess each loop
3. Prescribe fixes
4. Present findings

1. Discover Workflows

Find the top 3 workflows in this repo — both automated and manual. If the user specified a task ("I'm about to generate sprites"), prioritize workflows relevant to that task.

Run these scans:

Binary assets without generators — find committed images, fonts, audio, video, PDFs. Check if generation scripts, Makefiles, or asset pipelines produce them. If assets exist but no script generates them, that's a manual creation workflow.

Find: *.png, *.jpg, *.svg, *.gif, *.mp3, *.wav, *.pdf, *.ttf, *.otf
Then: look for Makefile, generate-*.sh, scripts/, or build steps that produce them
Missing generator = manual workflow

Git history churn — files re-committed with small changes repeatedly suggest a manual iteration loop. Look for binary files or config files with many commits.

git log --all --diff-filter=M --name-only --pretty=format: | sort | uniq -c | sort -rn | head -20

High re-commit count without associated test/script changes = manual iteration.

Human-in-the-loop scripts — scan shell scripts and docs for steps requiring visual inspection, manual input, or human judgment:

• Scripts that open a window/browser and wait for a human to look
• Steps phrased as "then you...", "manually...", "visually check...", "inspect the output"
• Scripts with read, open, sleep (waiting for human), or comments like "# check this looks right"

Workflow descriptions in docs — read CLAUDE.md, README, and contributing guides. Any multi-step process described in prose is a candidate. Pay attention to sequences like "first run X, then check Y, then run Z" — that's an unautomated pipeline.

Existing tap-audit — if .tap/tap-audit.md exists, read its feedback loops section. Don't redo that work, but check if its findings are still current.

2. Assess Each Loop

For each discovered workflow, evaluate four elements:

Element	Question
Generator	Can an agent produce the output? If not, what's missing — a skill, an MCP, a CLI tool, an API?
Evaluator	Can something other than the generator verify the output? Tests, lint, visual regression, Playwright, type checker, screenshot comparison?
Handoff	Can an agent context-reset and resume without losing progress? Shaped docs, plans, clear commit history, memory files?
Grading criteria	Are quality expectations measurable? Test suites, lint rules, acceptance criteria, dimension/palette specs, design specs? Or is it vibes?

Rate each workflow:

• Closed — all four elements present. Agent can iterate autonomously.
• Open — evaluator or grading criteria missing. Agent produces output but can't verify quality.
• No loop — no evaluator, no criteria. Agent guesses and hopes.
• Manual — human does this entirely by hand. No agent involvement yet.

3. Prescribe Fixes

For each non-closed workflow, prescribe a concrete automation path. Be specific about what to create:

• Skill to create — name it, describe what it does, what tools it needs. "Create a sprite-generation skill that uses image-gen MCP to produce pixel art PNGs, validates dimensions and palette against a spec, and renders in-app via dev-check.sh."
• MCP to wire up — which server, what it enables. "Add chrome-devtools MCP to enable visual regression testing of the rendered diorama."
• Hook to add — what event, what it does. "Add a PostToolUse hook on Write that validates PNG dimensions match the sprite spec."
• Tool to integrate — CLI tool, API, or service. "Install Playwright for browser-based acceptance testing of the onboarding flow."
• Test to write — what kind, what it covers. "Add acceptance tests using /design-acceptance-tests for the station assignment state machine."
• Grading criteria to define — measurable specs. "Define pixel art constraints: 32x32px, 4-color palette per character, .nearest filtering, specific pose set."

Don't prescribe generic improvements. Every recommendation should name a specific thing to build, wire, or configure.

4. Present Findings

Always open with the signature block:

`★ Loop Check ────────────────────────────────────`
[N] workflows assessed — [N closed] / [N open] / [N manual]
  ├─ [most impactful finding]
  ├─ [second finding]
  └─ [top recommendation to close a loop]
`─────────────────────────────────────────────────`

Then for each workflow, present the assessment and prescription. Lead with the manual and open workflows — closed loops don't need attention.

If everything is closed: say so and get out of the way. Don't invent problems.

Boundaries

• Does NOT write code, tests, or config — prescribes what to create, doesn't create it
• Does NOT assess infrastructure (CI/CD, permissions, test coverage stats — that's tap-audit)
• Does NOT produce a report file — output is conversational, not a document
• Does NOT auto-run — manual invocation only
• Findings are recommendations, not gates — nothing blocks the user from proceeding