Diagnose
Examine a codebase or diff for AI slop and produce a clinical report with a Slop Score. Use when the user asks to find AI slop, review code quality, clean up AI-generated code, run a health check or checkup on the repo, or audit recent agent-written changes. Combines a deterministic scanner (lab results) with guideline-based judgment (clinical examination).From its SKILL.md
npx -y skills add flopeztancredi/slopmd --skill diagnoseAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
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- 0 stars0 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.
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SKILL.md
4.5 KB, 973 tokens by cl100k_base, as published. Nobody here has run it
SlopMD: Diagnose
You are examining code for AI slop: the characteristic defects of AI-generated code. Your output is a clinical examination report. You do not fix anything in this skill; treatment is a separate step the user must ask for (the treat skill).
Step 1: Determine scope
- Default to diff scope when the repo has git history and the user said "my changes", "this PR", "recent work", or similar: examine only files changed vs the base (
git diff --name-only <base>, plus staged and untracked files). - Use full scope only when asked for the whole repo, or when the project is small (under roughly 50 source files).
- In diff scope, pre-existing problems in untouched code are NOT findings. Count them in one line of the Prognosis at most.
Step 2: Run the labs (deterministic scan)
Run the bundled scanner from this skill's directory:
node scripts/labs.js <path> --json # full scope
node scripts/labs.js <path> --json --diff <base> # diff scope
This returns objective findings (secrets, unpinned dependencies, emoji, typographic punctuation, type suppressions, broad catches, debug leftovers, and more) plus a preliminary Slop Score. These are lab results: report them as facts, do not re-litigate them. If a finding line carries slopmd-ignore, the scanner already skipped it.
Step 3: Clinical examination (judgment)
Read the in-scope files. For large scopes, prioritize: files the labs flagged, recently changed files, entry points, and the largest files. For each area of concern, load the matching reference and evaluate against it:
| Concern | Reference |
|---|---|
| Names, vocabulary drift | references/01-naming.md |
| Function size, nesting, decomposition | references/02-functions.md |
| Comments, docstrings | references/03-comments.md |
| Wrappers, patterns, premature abstraction | references/04-abstraction.md |
| Layering, placement, parallel structures | references/05-architecture.md |
| try/catch habits, silent failures | references/06-errors.md |
| Secrets, injection, authz | references/07-security.md |
| New dependencies, convention violations | references/08-dependencies.md |
| any-typing, magic values, null habits | references/09-types.md |
| Test quality | references/10-testing.md |
| Diff hygiene, prose slop | references/11-diff-discipline.md |
| Loops over queries, N+1, sequential awaits | references/12-performance.md |
Load only the references relevant to the code in scope. For a small diff that touches two functions, three references may be enough; a full-repo exam uses all twelve.
Step 4: Confidence gate
Score every judgment finding 0-100: "would a senior engineer who knows this project agree without hesitation?" Report only findings at 80 or above. Never report:
- Style the project uses consistently and deliberately, even if the guidelines disagree. Local convention wins.
- Anything the project's linter or formatter already governs.
- Speculative improvements ("could be more flexible"). SlopMD removes speculation, it does not add it.
- Duplicate reports of one root cause. Group them.
Step 5: The examination report
Produce the report in this exact structure, plain ASCII, no emojis:
SLOPMD EXAMINATION
Patient: <repo or diff description> Scope: <diff|full> Files examined: N
VITAL SIGNS (lab results)
Slop Score: NN/100 (<verdict>)
<counts by severity, one line>
<top lab findings, file:line, max ~10 lines>
SYMPTOMS (clinical findings)
For each finding:
[category] file:line (confidence NN)
<one-line defect statement, citing the violated rule>
<one-line evidence or snippet>
DIAGNOSIS
<2-4 sentences: the root causes behind the symptoms. Which habits or
generation patterns produced this? What is the single biggest risk?>
PRESCRIPTION
<numbered treatment plan, highest value first. Each item is small,
independently applicable, and states the intended diff. Security
criticals always come first.>
PROGNOSIS
<1-3 sentences: expected state if treated vs untreated, and the
projected Slop Score after treatment.>
Close by offering to apply the prescription with the treat skill. Do not start treating without being asked.
What ships with it: 13 files
59.3 KB alongside SKILL.md, 1 of them executable
references/
- 01-naming.md1.8 KB
- 02-functions.md2.0 KB
- 03-comments.md2.0 KB
- 04-abstraction.md2.6 KB
- 05-architecture.md2.1 KB
- 06-errors.md2.0 KB
- 07-security.md1.9 KB
- 08-dependencies.md2.1 KB
- 09-types.md1.8 KB
- 10-testing.md1.7 KB
- 11-diff-discipline.md2.2 KB
- 12-performance.md2.3 KB
scripts/
- labs.jsruns34.6 KB
Gives 0 of the 12 instructions most debug triage skills give in 973 tokens
Counted across 839 of the 1,149 authors here whose files we hold, read 2026-08-07
- Investigate root cause before proposing any fixin 102 of 839, across 67 files
- Read error messages completelyin 89 of 839, across 49 files
- Create a failing test case before fixingin 84 of 839, across 46 files
- Reproduce the issue consistentlyin 82 of 839, across 41 files
- Change one variable at a timein 82 of 839, across 42 files
- Check recent changesin 74 of 839, across 36 files
- Write the regression test before fixingin 74 of 839, across 40 files
- Fix the root cause not the symptomin 60 of 839, across 45 files
- Implement a single fix at a timein 59 of 839, across 20 files
- Trace data flow backward to the sourcein 50 of 839, across 20 files
- Remove all debug instrumentationin 49 of 839, across 13 files
- Form a single hypothesisin 48 of 839, across 18 files
Said here and by no other author read
- examine code for characteristic defects of AI-generated code
- default to diff scope for recent changes
- ignore pre-existing problems in untouched code
- run the deterministic scanner to get lab results
- report lab results as facts
- read in-scope files to perform clinical examination
Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.