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The selection guideSource-backed research ↗
Schema & Structured Data / AI-search readiness linter
geolint
An open-source linter for AI-search readiness, crawler access, llms.txt, structured data, and citability
Technical SEOAI-search readinessDeveloper tooling
Why it stands out
Open-source and locally runnable with MIT licensing.
Source review: · Public-source research, not a hands-on test
New open-source project; evidence supports capabilities and distribution, not citation or traffic outcomes.
↗ Best for
Technical SEO teams adding AI crawler and structured-data checks to pull requests.
! Know before you buy
The score is geolint's own diagnostic summary. No reviewed source proves that its rules predict AI citations, traffic, rankings, conversions, or revenue.
01 / Editorial assessment
Is geolint for you?
The AICiteKit take
geolint is a cautious medium-confidence choice for developers and technical SEOs who want repeatable AI-search readiness checks in local or CI workflows. Its public repository documents rule IDs, matched evidence, output formats, GitHub Action support, and an MCP server, while npm confirms a published package. OpenSSF adds independent security and maintenance context but also reports a dated 3.3 score, recent-project warning, and dependency vulnerabilities. geolint should be treated as a technical diagnostic: its score is author-defined and no reviewed source proves that fixing a finding increases citations, traffic, rankings, or conversions.
A good fit if you are…
- Technical SEO teams adding AI crawler and structured-data checks to pull requests.
- Developers who prefer a local CLI and machine-readable output over a hosted dashboard.
- Agencies that need repeatable technical baseline reports with explicit evidence boundaries.
- GitHub Actions teams using SARIF, Markdown, JSON, or HTML audit artifacts.
Consider another option if…
- Brand teams seeking prompt monitoring, historical answer archives, or competitor share of voice.
- Buyers requiring a documented model panel, geography controls, SLA, hosted support, or client portal.
- Teams that interpret a readiness score as a search-engine ranking or citation guarantee.
- Production pipelines that cannot review Node.js and dependency/security requirements.
02 / Scope, not promises
Features & coverage
- Runtime
Node.js 22 or newer according to the repository and npm package metadata
Archived research · Research verified 2026-11-01Research excerpt · Quick facts- Rule coverage
52 documented rules across AI crawler access, llms.txt, structured data, citability, and technical foundation categories
Archived research · Research verified 2026-11-01Research excerpt · Quick facts- Current package
@iliasabk/geolint version 0.4.0 in npm metadata checked 2026-11-01
Archived research · Research verified 2026-11-01Research excerpt · Quick facts- Outputs
Pretty terminal output plus JSON, SARIF, Markdown, and self-contained HTML reports
Archived research · Research verified 2026-11-01Research excerpt · Quick facts- Integrations
GitHub Action, CI thresholding, MCP server, and npx/npm installation are documented
Archived research · Research verified 2026-11-01Research excerpt · Features and practical implications- Independent signal
OpenSSF Scorecard snapshot dated 2026-10-27 reported score 3.3, recent-project warning, and dependency vulnerabilities; this is dated context, not a product-quality rating
Archived research · OpenSSF snapshot date 2026-10-27Research excerpt · Pricing, installation, and limits
AI crawler access checks
The repository documents purpose-aware checks for known AI crawler tokens and robots directives. This supports a technical access audit; it does not prove a vendor will crawl, retrieve, or cite a page.
llms.txt and structured data
geolint checks llms.txt structure and selected JSON-LD conditions, and documents that llms.txt is a proposal rather than a universally adopted standard. Generated files and schema still require review.
CI and machine-readable reports
JSON, Markdown, HTML, and SARIF outputs plus GitHub Action support can fit pull requests, code scanning, and internal quality gates. Thresholds are internal policies, not search metrics.
Citability diagnostics
The documented rules cover content signals such as thin content, headings, dates, and question-shaped structure. These are heuristics and cannot establish causal citation improvement.
A focused evaluation workflow
- Pin the package version and record the rule list and configuration.
- Run the same URL locally and in CI, preserving JSON or SARIF reports.
- Inspect high-severity findings against the actual robots, HTML, JSON-LD, and sitemap responses.
- Review generated llms.txt, schema, and content recommendations before committing changes.
- Pair technical reports with a fixed prompt panel when measuring actual answer visibility.
03 / Commercial boundaries
Pricing & limits
Terms below reflect the 2026-11-01 source review, not a new live quote. Confirm currency, billing term, tax and required scope with the provider.
- Software price
No hosted subscription price is documented in the reviewed sources; the MIT-licensed CLI/package is available for local use. Runtime, CI, network, and connected-service costs remain the buyer's responsibility.
Archived research · Research verified 2026-11-01; confirm current package and repository termsResearch excerpt · Pricing, installation, and limits
- Access model
Open-source MIT repository and published npm package; no proof of a hosted unlimited monitoring service.
Archived research · Research verified 2026-11-01Research excerpt · Quick facts
Your buying checklist
Get these answers first.
- Which rules are errors, warnings, or heuristics in the version I am pinning?
- Does the target site need a local crawl, CI check, GitHub Action, or MCP workflow?
- How will I preserve raw reports and compare results after a rule-set update?
- What separate evidence will show retrieval, citation, traffic, or conversion changes?
- Have current npm advisories and the OpenSSF snapshot been reviewed before production use?
Pricing context & qualifications
Verified 2026-11-01 from npm metadata and the official repository. No hosted pricing tiers or SLA were documented; local runtime and CI costs remain outside the package.
04 / The tradeoffs
Strengths & weaknesses
Reasons to shortlist
- Open-source and locally runnable with MIT licensing.
- Findings expose rule IDs, evidence, severity, and suggested fixes.
- JSON, Markdown, HTML, and SARIF outputs fit CI and code-scanning workflows.
- The repository documents both supported checks and important limitations.
- GitHub Action and MCP paths make the checks accessible to engineering workflows.
Reasons to pause
- The score and weighting are geolint-defined, not search-engine metrics.
- No reviewed source proves citation lift, AI referral growth, rankings, or conversions.
- No prompt-monitoring history, answer archive, or competitive visibility panel is documented.
- OpenSSF's October 27 snapshot reported a 3.3 score, recent-project warning, and vulnerabilities; re-check before production adoption.
- Generated llms.txt, schema, and content fixes require human technical and editorial review.
The score is geolint's own diagnostic summary. No reviewed source proves that its rules predict AI citations, traffic, rankings, conversions, or revenue.
05 / Choose by the job
Alternatives to consider
Editorial fit comparisons—not performance rankings or claims that one option always wins.
06 / What we can substantiate
Reviews & evidence
No independent product-specific review sample or efficacy study was found. npm confirms public distribution and OpenSSF provides a dated external security/maintenance signal, but neither is a customer satisfaction or AI-search outcome rating.
Official repository
Author-controlled documentation; not independent efficacy evidence.
Snapshot: 2026-11-01 · View source
npm registry
Distribution does not prove reliability, satisfaction, or outcome lift.
Snapshot: 2026-11-01 · View source
OpenSSF Scorecard
Dated 2026-10-27; reports a low score and vulnerabilities, and is not a product rating.
Snapshot: 2026-11-01 · View source
AICiteKit assessment: public-source research, not a hands-on product test. Official materials establish stated scope; reviews are dated and may concern the broader platform. Neither establishes guaranteed citations, traffic or revenue.
Sources & original verification dates
| Source | Evidence type | Checked |
|---|---|---|
| geolint official GitHub repository ↗ | Official product documentation | |
| geolint rule documentation ↗ | Official methodology documentation | |
| geolint npm registry metadata ↗ | Independent distribution registry | |
| OpenSSF Scorecard for geolint ↗ | Independent security and maintenance signal | |
| geolint GitHub releases ↗ | Official release history |
Original review evidence & date context
Preserved from the published research. Dates, review counts and product-scope qualifications below have not been refreshed by this layout migration.
Official GitHub repository and rule docs support capabilities; npm provides independent distribution metadata; OpenSSF provides an independent dated security/maintenance snapshot. None proves AI-search outcomes.
Research notes & unresolved discrepancies
- Evidence is sufficient for a cautious listing of an active open-source tool.
- No independent customer-review sample, efficacy study, or citation-lift experiment was found in the directly checked sources.
- Do not invent a rating or user consensus.
Layout migration: October 4, 2026. The original MDX research is retained in the repository; this reorganization does not refresh its factual verification dates.