lint
Skill0 starsChanged 3 months agoMITView on GitHub
Health-checks the wiki. Finds orphans, broken links, contradictions, stale claims, missing pages, and index drift, then offers to fix them. Use when the user runs /lint, asks whether the wiki is healthy, or after a batch of ingests.
80 other projects use a version of this.
Adopted by
Most recently taken up by
- PMDevSolutions/Flaviantheir own version, first seen Nov 8, 2026
- aiagentkit-labs/agentic-dev-kittheir own version, first seen Nov 8, 2026
- levi-qiao/obsidian-llm-wikitheir own version, first seen Nov 8, 2026
- elastic/docs-buildertheir own version, first seen Nov 4, 2026
- DataDog/dd-trace-pytheir own version, first seen Nov 1, 2026
- PMDevSolutions/Aureliustheir own version, first seen Nov 1, 2026
Used with
Projects with it also use query, coverage and 8 more.
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Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
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Other versions80 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 80
- ray-project/ray★ 44ksame name
- FalkorDB/FalkorDB★ 10ksame name
- FastLED/FastLED★ 7.5ksame name
- fleetdm/fleet★ 7.2ksame name
- aaddrick/claude-desktop-debian★ 5.5ksame name
- cloudposse/atmos★ 1.4ksame name
- ethereum/execution-specs★ 1.2ksame name
- adobe/S3Mock★ 1.2ksame name
- maxGraph/maxGraph★ 1.2ksame name
- jason-effi-lab/karpathy-llm-wiki-vault★ 718same name
70 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository23 other files it gives its agents.
- CLAUDE.mdCLAUDE.md
- remotion-best-practicesSkill
- add-inspirationSkill
- brandSkill
- craft-contentSkill
- draft-articleSkill
- draft-carouselSkill
- draft-diagramSkill
- draft-imagesSkill
- draft-videoSkill
- heygen-avatarSkill
- heygen-videoSkill
- humanizerSkill
- ingestSkill
- initSkill
- linkedin-postSkill
- listenSkill
- meetingSkill
- voiceSkill
- wikiSkill
- youtube-descriptionSkill
- youtube-shortSkill
- youtube-uploadSkill
The file
We split this skill into the rules it gives an agent
4 rules. 0 are common, 2 are distinctive, and 2 are very specific to this project.
0
Common
Most of the 67 edited versions we read keep these.
2
Distinctive
This author's own choices. Worth a look.
2
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 12
Run this every ten ingests, monthly at minimum, and before leaning on the wiki for anything large.
- Very specific: line 17
Read .amplifyrc for paths.wiki and paths.sources, and {vaultPath}/CLAUDE.md for the conventions being checked against.
- Very specific: line 22
Read every page under {wiki}/.
- Distinctive: line 29
Run the script rather than doing these by hand:
“Common” is measured: kept by at least 6 in 10 of the 67 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Lint the Wiki
Wikis rot quietly. A page nothing links to is a page nobody finds again; an index entry pointing at a deleted file is worse than no entry. None of this announces itself, so it has to be checked on purpose.
Run this every ten ingests, monthly at minimum, and before leaning on the wiki for anything large.
Step 0: Load configuration
Read .amplifyrc for paths.wiki and paths.sources, and {vaultPath}/CLAUDE.md for
the conventions being checked against.
Step 1: Build the picture
Read every page under {wiki}/. For each, collect the filename, the # Title, the
frontmatter, and every [[link]] in the body. Then compute the inbound links for
each page. Do the mechanical parts with a script rather than by reading — this part
is bookkeeping, not judgment.
Step 2: The mechanical checks
Run the script rather than doing these by hand:
npm run lint:wiki # counts, plus every structural failure
npm run lint:wiki -- -v # also lists orphans and empty-source pagesIt covers broken links, index drift in both directions, missing aliases, dangling sources, and orphans. It exits non-zero on structural breakage and treats orphans and empty sources as reportable rather than failing, since a page written a minute ago is legitimately both. What follows is what it checks, for when you need to reason about a finding rather than just see it.
Orphans. Pages with zero inbound links from any other page. The index does not count — being listed is not being connected.
Broken links. [[Targets]] with no page of that title. Usually a rename that did
not propagate, or a link written from the filename instead of the title.
Wrapped links. A [[link]] split across a line break does not resolve, and it reads
as correct in the source — the only symptom is the target showing up as a broken link
whose name contains a newline. Worth checking for explicitly, since hard-wrapped prose
produces it constantly.
Index drift. Pages on disk missing from index.md, and index entries naming pages
that no longer exist.
Dangling sources. A page whose sources frontmatter names a file that is not in
{sources}/. Means the audit trail is broken.
Frontmatter violations. Missing tags, sources, created, updated, or
aliases. Extra fields that are not in the schema. An empty sources list on anything
but a synthesis page, which means the page is unsupported opinion.
Missing aliases. A page whose aliases does not contain its own # Title. This is
the highest-value mechanical check in the list: links are written from the title while
filenames are kebab-case, so a page without its alias cannot be linked to at all, and it
will read as an orphan for a reason that has nothing to do with how well it is connected.
Naming. Filenames that are not kebab-case, titles that are not Title Case, links
written as [[some-file-name]] instead of [[Some File Name]].
Step 3: The judgment checks
These need reading, not scripting.
Contradictions. Two pages asserting incompatible things. Report both, with the sources behind each. Do not resolve it yourself.
Stale claims. A page whose updated predates a source that bears on it. Especially
where a newer clipping in {sources}/ was never worked into the pages it touches.
Missing pages. A concept, person, or tool named across three or more pages with no page of its own. That is the wiki asking for a page.
Missing cross-references. Pages that clearly relate and do not link. Common after a batch ingest where each source was filed without looking sideways.
Step 4: Report
Group by severity. Lead with counts so the trend is visible across runs.
Wiki health — [N] pages
Broken [N] broken links, [N] dangling sources
Index [N] pages missing, [N] stale entries
Orphans [N] pages with no inbound links
Schema [N] frontmatter violations, [N] naming violations
Judgment [N] contradictions, [N] stale pages, [N] missing pagesThen list each finding with the file it is in and the specific fix. Be concrete — "add a link from [[A]] to [[B]]" beats "improve cross-referencing".
Step 5: Offer to fix
Mechanical fixes can be applied in a batch once the user agrees: index rebuilds, link-casing corrections, frontmatter backfill, kebab-case renames.
Judgment findings need the user. Contradictions in particular are theirs to resolve — picking a side automatically is how a wiki starts quietly lying.
Step 6: Log the pass
Append to {wiki}/log.md:
## [YYYY-MM-DD] lint | [N] pages checked
[N] orphans, [N] broken links, [N] contradictions. Fixed [what]. Left [what] for review.Log every pass, including a clean one. The value is the trend: orphan count creeping up means ingests are being filed without linking sideways.
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
No reviews yet
People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
- Partly
- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

