Pseolint

The only tool purpose-built for programmatic SEO compliance. It shifts the unit of analysis from URL to template: point it at a 10,000-URL pSEO directory and pseolint identifies the template clusters (e.g. /listing/:slug, /category/:slug), samples K pages from each, and produces a per-template verdict + variance metric. Fix one template, fix N pages.

npx pseolint http://localhost:3000

• Why this exists
• How pseolint differs
• Quick Start
• What It Checks: the 65 rules
• CLI Options
• GitHub Action
• Fix rail: from audit to pull request
• Skills for Claude & coding agents
• Roadmap
• Contributing

Skills for Claude & coding agents (new)

Design pages that pass before you crawl them. The skills/ suite gives Claude (and any agent that supports the skills / Claude Code plugin format) programmatic-SEO and answer-engine optimization (AEO / GEO) guidance where every recommendation is bound to a runnable pseolint rule:

npx skills add ouranos-labs/pseolint --skill pseolint aeo

• pseolint: full-lifecycle programmatic SEO: design → build → audit → fix → gate.
• aeo: get cited in AI Overviews / ChatGPT / Perplexity, not just ranked.

Unlike prose checklists, these have teeth: the design-time advice ends in npx pseolint pass/fail. See skills/README.md.

Why this exists

Programmatic SEO works, when it works. The gap between "1,000 indexed pages" and "1,000 pages that survive a SpamBrain pass" is where most pSEO sites die. The Helpful Content Update made that gap permanent.

Existing SEO tools (Screaming Frog, Sitebulb, Ahrefs Site Audit) were built for editorially-curated sites. They check pages one at a time. But the SpamBrain risks of pSEO are between pages: doorway clusters, near-duplicates, entity-swap templates, thin-content propagation. You can't catch them with per-page rules.

pseolint audits the graph: it groups results by template before surfacing them. Run it before you publish, gate it in CI, fix the broken template before SpamBrain does.

How it compares

The general-purpose crawlers do plenty pseolint doesn't (JS rendering at scale, backlink data, log-file analysis). pseolint is the specialist for the one thing they weren't built for: programmatic-SEO compliance at the template level.

How pseolint differs

• Graph-level, not page-level. Detects near-duplicate clusters, doorway patterns, and entity-swap doorways across thousands of pages. Per-page tools can't see these.
• SpamBrain + AI Overview. 65 rules across 8 categories: SpamBrain-policy mapping (penalty risk) plus aeo/* (AI Overview citability: llms.txt, AI-crawler access, citable facts, answer-first, summary-bait).
• Developer workflow, not SaaS UI. CLI, GitHub Action, JSON/HTML reports, MCP server, browser extension (SERP competitive recon). Lives in your repo and your PRs.
• Actionable, not advisory. Every finding has a fix, an effort tag (quick fix / moderate / structural), and a Google docs reference.
• Safe for hosted use. SSRF guard (DNS-validated), robots.txt honoured for our own crawler, analytics-blocking in render mode, AbortSignal cancellation, safeMode: "saas" preset for embedding in services.
• Calibrated against reputable pSEO. Engine verdicts are calibrated against a curated corpus of in-production pSEO sites that demonstrably win in search. Doorway-pattern findings cluster (no more per-pair noise); verdicts are reproducible at a fixed sampleSeed. Dated snapshot results, the open-source corpus, and the trade-offs we accepted live at pseolint.dev/methodology. Spec: docs/superpowers/specs/2026-05-03-calibration-against-reputable-pseo.md.
• Authority-blind by design, with a manual override. pseolint analyses static content + the link graph it can see. It does NOT measure backlinks, brand mentions, domain age, or any external trust signal: there is no Moz/Ahrefs/Semrush dependency. This means the engine itself is calibrated for the authority tier of the calibration corpus (established brands). It exposes authorityScore (0-100, via the --authority-score CLI flag, the core API, or the MCP param) so callers can adjust the verdict ladder for their tier: >= 80 shifts one tier lenient (established brand can absorb shapes a newer site can't); <= 30 shifts one tier stricter. Raw risk number unchanged so CI gates stay stable. Without the flag, treat verdicts as a directional minimum.
• Honest about blind spots. Beyond domain authority, pseolint does not currently detect: image SEO dimensions, schema-content drift (e.g. JSON-LD price ≠ rendered price), outbound-link health, search-intent alignment, parameter-URL crawl-budget waste, and a handful of specialty gaps (mobile-friendliness, cookie-banner detection, AMP/News/Video schema). The complete blind-spot audit lives at : every gap categorized by impact tier with the roadmap fix.

Full version history (calibration rounds, per-rule changes, safety hardening) is in CHANGELOG.md.

Grow: make the ignored pages rank (no backlinks)

A pSEO site rarely has a penalty problem. It has a Google-ignores-most-of-it problem: thousands of sitemap URLs, a few percent earning impressions. Backlinks are not the only lever. Search Console already records which of your pages Google chose to show. pseolint grow reads that, crawls the site, and learns what separates shown pages from ignored ones within the same template. Each site is its own control group, so domain authority cancels out. Then it writes the plan.

# Search Console → Performance → Pages → Export (last 3 months) → Pages.csv
npx pseolint grow https://yoursite.com --gsc Pages.csv --out growth/

What you get:

• Show rate per template. The pSEO number that matters: /city/:slug 4,200 pages, 3% shown.
• What Google rewards on this site. Shown vs ignored pages per template, compared with a Mann-Whitney U test and Benjamini-Hochberg false-discovery control. Example: "Shown pages have MORE internal PageRank: 0.51 vs 0.38 (AUC 0.85)", or "LESS similarity to sibling pages: 70% vs 85%". Only differences that survive the correction are printed.
• A link plan (links.csv). Every link goes from → to with its anchor. Links start on pages Google already shows, because those get recrawled, and point to topically related pages that sit at positions 8-30 or get no impressions at all. Existing links are never re-suggested.
• Title rewrites (retitle.csv). Pages ranking in the top 15 whose CTR is under half the expected CTR for that position.
• Self-inflicted gaps. Sitemap URLs that are noindex, canonicalised away or erroring (unblock.csv), and pages earning impressions that the sitemap forgot (sitemap-additions.txt).
• Differentiate / prune. Ignored near-clones of their siblings, and templates Google rejects wholesale (under 5% shown).

Then tell the engines that index on request:

# Serve https://yoursite.com/<key>.txt containing the key, then:
npx pseolint indexnow https://yoursite.com --key <key> --since 7

IndexNow reaches Bing, Yandex, Seznam and Naver, and Bing's index also feeds ChatGPT search and DuckDuckGo. Google ignores IndexNow, and its Indexing API only accepts job and livestream pages. For Google, the levers are the link plan and an accurate sitemap lastmod.

Re-run grow monthly with a fresh export. The template show rates are your scoreboard.

Quick Start

# Point it at your local dev server: that's it
npx pseolint http://localhost:3000

Automatically discovers all pages by following internal links. No sitemap, no config, no build step needed.

# Save a visual report
npx pseolint http://localhost:3000 --format html --output report.html

# Audit a live site (per-template output is the default)
npx pseolint https://yoursite.com

# CI gate on build output
npx pseolint ./out --ci-threshold concerning --format json

Per-template output (v0.6 default)

Verdict: CONCERNING
Integrity C · Discoverability B · Citation C · Data A

Per-template breakdown (3 templates):

  /listing/:slug  CONCERNING  C
  10/8201 URLs (0.1%)  uniformity 85%
  8/10 samples fail `spam/thin-content`

  /category/:slug  READY  A
  10/312 URLs (3.2%)  uniformity 94%

  /help/:slug  CAUTION  B
  10/47 URLs (21.3%)  uniformity 78%
  3/10 samples fail `content/missing-author`

--format json includes the templates array alongside the existing findings list:

{
  "verdict": "concerning",
  "risk": 60,
  "templates": [
    {
      "signature": "/listing/:slug",
      "totalUrls": 8201,
      "auditedUrls": ["https://example.com/listing/foo", "..."],
      "verdict": "concerning",
      "risk": 60,
      "variance": {
        "uniformityScore": 0.85,
        "topDriver": { "ruleId": "spam/thin-content", "fireRate": 0.8 }
      }
    },
    { "signature": "/category/:slug", "verdict": "ready", "risk": 12 }
  ],
  "findings": [...]
}

Use --legacy-flat to suppress the template cards and get the v0.5-style flat findings list.

Partial coverage (truncated)

If the crawl is interrupted (e.g. the backpressure watchdog aborts because the origin is degrading), pseolint still emits whatever it collected, flagged as partial:

{
  "verdict": "ready",
  "risk": 12,
  "truncated": true,
  "truncatedReason": "Origin degraded mid-crawl (p95 latency exceeded threshold)",
  "pageCount": 42
}

When truncated is true, treat pageCount, risk, and verdict as lower bounds: a partial pass is not a full pass. The CLI prints a PARTIAL REPORT banner and exits non-zero; the GitHub Action warns (and can fail with fail-on-truncated: true); the MCP tools and web report surface the same flag. Programmatic consumers should branch on it. The full output contract is published as a JSON Schema (packages/core/schemas/audit-summary.schema.json, $id carries the schemaVersion).

Audit Modes

Why localhost is recommended: Build directories contain framework artifacts (Next.js [slug].html shells, empty client-rendered pages) that produce false positives. Your dev server renders the actual pages Google will see: with canonicals, meta tags, and full content.

What It Checks

65 rules across 8 categories (all 8 scored), producing a weighted SpamBrain Risk Score (0-100) and an independent AEO sub-score for AI Overview citability. Every rule is backed by a primary source (Google Search Central, sitemaps.org, ogp.me, Lighthouse); the checks we deliberately refuse to run (folklore the primary sources contradict, like title/description character limits) live in docs/folklore.md:

SpamBrain Risk Detection

Content Quality

Internal Linking

Technical SEO

Data Consistency

Structured Data

Cannibalization

cannibal/title-overlap and cannibal/keyword-collision were dropped in v0.4 due to high false-positive rates on legitimately similar pages (e.g. localized variants, paginated archives). See the v0.4 redesign spec §4.3.

AEO: AI Overview Readiness (v0.3.x)

Live URL Scanning

When you point pseolint at a URL, it captures what Google sees:

• HTTP metadata: status codes, redirect chains, X-Robots-Tag, Link headers
• Crawl discovery: follows internal links from the start page to find all crawlable pages
• Sitemap comparison: if a sitemap exists, compares it against crawl-discovered pages

# Just give it your homepage: it discovers everything
npx pseolint https://paperforge.dev

Page Groups

Different page types need different standards. Configure groups in pseolint.config.ts:

export default {
  pageGroups: {
    pseo: {
      match: '/templates/**',
      rules: ['spam/*', 'content/*', 'links/*', 'cannibal/*', 'tech/*', 'schema/*'],
      overrides: {
        'spam/thin-content': { thinContentMinWords: 500 },
      }
    },
    listing: {
      match: ['/documents', '/templates'],
      rules: ['tech/*'],
    },
    marketing: {
      match: ['/', '/about', '/pricing'],
      rules: ['tech/*'],
    },
    utility: {
      match: ['**/404*', '**/500*'],
      rules: [],  // skip entirely
    }
  }
};

Each group gets its own score. Unmatched pages get all rules.

SpamBrain Risk Score

The risk score (0–100) aggregates rule penalties into 4 super-categories (Integrity (spam + content + cannibal), Discoverability (links + tech), Citation (aeo + schema), and Data) with site-type-aware weights, so a programmatic directory and a docs site are each scored against the rule weighting that matches their archetype. Since v0.6, scoring runs per template and rolls up to a site verdict: the worst-scoring template that covers ≥5% of the audited URLs.

The score maps to a 4-rung verdict ladder, and CI gates on the verdict (--ci-threshold, default concerning), not a raw numeric band:

See pseolint.dev/methodology for the calibrated weights and verdict thresholds.

Actionable Output

Findings are automatically enriched before display:

• Pairwise clustering: Thousands of near-duplicate pair comparisons collapse into a handful of cluster findings: "48 pages form a near-duplicate cluster (86–94% similar)."
• Content breakdown: Each cluster shows what's shared vs. unique: "Shared: description of property (31w), buyer acknowledges (35w). Unique: 3324w of 8140w."
• Effort tags: Every finding is tagged quick fix, moderate, or structural so you know where to start.
• Template detection: When the tool detects template-generated content, fix suggestions speak to template authors: "Add conditional content sections per entity."

CLI Options

Usage: pseolint [options] [command] [source]

Arguments:
  source                         URL or directory path to audit

Output
  -f, --format <type>            Output format: console | json | markdown | html (default: console)
  --ci-threshold <severity>      Min verdict that fails CI: ready|caution|concerning|critical (default: concerning)
  -t, --threshold <n>            [deprecated] Numeric risk threshold; use --ci-threshold instead
  -o, --output <file>            Write report to file instead of stdout
  --no-color                     Disable colored output

Crawl / fetch
  --concurrency <n>              Max parallel HTTP fetches (default: 5)
  --timeout <ms>                 Per-request timeout in ms (default: 30000)
  --no-crawl                     Disable crawl-based page discovery for URL sources
  --ignore <patterns>            Comma-separated glob patterns to exclude
  --render                       Render pages in a browser before auditing
  --browser-ws <url>             CDP WebSocket endpoint for browser rendering

Sampling
  --sample-size <n>              Audit N pages (default: 0 = all)
  --strategy <random|stratified> Sampling strategy (default: stratified)
  --max-per-template <n>         Cap samples per URL template cluster (default: 0)

Template output (v0.6)
  --per-template                 Render per-template cards above the findings list (default: ON)
  --template <signature>         Filter output to a single template, e.g. /listing/:slug
  --legacy-flat                  Suppress template cards; print the v0.5-style flat findings list

Cache & monitoring
  --cache [dir]                  Enable HTTP cache (default: .pseolint/cache)
  --cache-ttl <duration>         TTL for entries without validators, e.g. 7d, 1h, 30m (default: 7d)
  --state [path]                 Enable state persistence (default: .pseolint/state.json)
  --mode <monitoring|fresh>      v0.5+ change-driven monitoring mode. Auto-monitoring is the
                                 default when prior state exists. Use 'fresh' to force a full
                                 re-audit even with prior state.
  --age-floor-days <n>           v0.5+ minimum days since a URL's last fetch before monitoring
                                 forces a re-fetch regardless of other signals (default: 7)
  --since                        v0.5+ alias for --mode=monitoring (kept for back-compat)
  --exit-on-regression           Exit non-zero when new rule IDs fire vs prior --state

Data
  --data-source <file>           JSON file with source data for content-verification rules

AI triage (opt-in)
  --ai                           Enable AI triage of findings
  --ai-provider <id>             anthropic | openai | google | mistral | groq | xai | cohere | ollama
  --ai-model <name>              Model name (overrides provider default)
  --ai-endpoint <url>            AI endpoint (Ollama only; default: http://localhost:11434)
  --ai-max-tokens <n>            Input token cap per triage call (default: 60000)
  --ai-max-cost <usd>            Refuse a triage call whose pre-flight cost exceeds this USD
  --ai-daily-budget <usd>        Refuse triage when today's total spend would exceed USD (requires --telemetry)
  --ai-cache-ttl <duration>      Triage cache TTL, e.g. 30d, 12h, 60s (default: 30d)
  --no-ai-cache                  Bypass AI triage cache for this run
  --no-ai-suggest                Suppress AI discovery hint in non-AI runs

Telemetry (local, offline)
  --telemetry                    Enable local telemetry write (.pseolint/telemetry.jsonl)
  --telemetry-path <file>        Override telemetry JSONL path
  --no-telemetry-prompt          Suppress the y/n/skip triage feedback prompt
  --triage-feedback <rating>     Non-interactive feedback: helpful | unhelpful | y | n

MCP
  --mcp                          Start as an MCP server (for AI coding assistants)

Commands:
  stats                          Show aggregate telemetry stats from .pseolint/telemetry.jsonl
  stats-export <outPath>         Copy telemetry JSONL to <outPath> for manual review/sharing

Caching & change-driven monitoring (v0.5)

# First run: populates .pseolint/cache and .pseolint/state.json with full baseline
npx pseolint https://yoursite.com --cache --state

# Subsequent runs auto-enter monitoring mode. The decision matrix decides which
# URLs to fetch BEFORE the network round-trip:
#   - new URL                         → fetch (reason: new)
#   - prior fetch ≥ 7 days old        → fetch (reason: age)
#   - ruleset version bumped          → fetch (reason: ruleset)
#   - prior warning/error finding     → fetch (reason: recheck): info findings carry forward
#   - sitemap <lastmod> newer         → fetch (reason: lastmod)
#   - none of the above + lastmod present → SKIP (carry findings forward)
npx pseolint https://yoursite.com --cache --state

# Force a full re-audit even with prior state
npx pseolint https://yoursite.com --cache --state --mode=fresh

# Lower the age-floor for tighter monitoring (default: 7 days)
npx pseolint https://yoursite.com --cache --state --age-floor-days=3

# CI gate that fails when a *new* rule ID starts firing on actually-fetched URLs
npx pseolint https://yoursite.com --cache --state --exit-on-regression

Sites whose sitemaps emit <lastmod> (Next.js, Yoast/WordPress, Astro) get the biggest savings: typically ~95% fewer fetches on steady-state monitoring runs. Sites without <lastmod> hit no-signal and refetch every URL; bandwidth is still saved via cache.ts conditional GETs but round-trips aren't skipped (a HEAD-fallback path is on the roadmap).

End-of-run summary line:

Monitoring: 47/4012 URLs re-scraped (recheck=23, lastmod=12, age=8, new=4), 3965 carried forward.

AI triage

Turns hundreds of findings into a handful of ranked root causes. Opt-in, bring-your-own API key, with cost guardrails:

# Auto-detect provider from env (ANTHROPIC_API_KEY, OPENAI_API_KEY, etc.)
npx pseolint https://yoursite.com --ai

# Pin provider + model, cap spend
npx pseolint https://yoursite.com --ai \
  --ai-provider anthropic \
  --ai-model claude-haiku-4-5 \
  --ai-max-cost 0.50

# Local-only (Ollama, no network cost)
npx pseolint https://yoursite.com --ai --ai-provider ollama --ai-model qwen2.5:7b

# Enforce a daily spend ceiling across runs (requires telemetry)
npx pseolint https://yoursite.com --ai --telemetry --ai-daily-budget 5.00

Every call prints a pre-flight cost estimate before hitting the provider. Cache hits don't count against the daily budget.

Local telemetry & stats

Telemetry is local JSONL only: zero network, counts + spend + feedback ratings. Off by default.

npx pseolint https://yoursite.com --ai --telemetry
npx pseolint stats              # show your success rate, spend, feedback ratio
npx pseolint stats-export out.jsonl  # copy log for manual inspection

Browser Rendering

For client-rendered sites (React SPAs, Next.js app router), use --render to capture the fully rendered DOM:

# With a remote CDP endpoint (Browserless, etc.)
PSEOLINT_BROWSER_WS=wss://your-browser:3000 npx pseolint https://yoursite.com --render

# With local Playwright
npm install playwright-core
npx playwright install chromium
npx pseolint https://yoursite.com --render

Works with any CDP-compatible browser. Remote endpoints must use wss://.

Core Web Vitals

Two sources, both opt-in:

# Lab: measure LCP + CLS from a headless-Chromium render. Zero external calls.
npx pseolint https://yoursite.com --render

# Field: real-user p75 LCP/CLS/INP from the Chrome UX Report (the numbers Google
# ranks on, and the only source of INP). Free key: https://developer.chrome.com/docs/crux/api
CRUX_API_KEY=... npx pseolint https://yoursite.com          # or --crux-api-key <key>

# Query the mobile field data specifically (Google indexes mobile-first)
CRUX_API_KEY=... npx pseolint https://yoursite.com --crux-form-factor phone

Selection is per-metric: when a CrUX key is set, tech/core-web-vitals uses field data for each of LCP/CLS/INP and falls back to the lab render for any metric CrUX lacks, so enabling field data never drops a signal the lab render already had.

CrUX only covers URLs/origins with enough real traffic, so low-traffic pSEO pages get their origin-level field vitals as a fallback. A site-wide origin reading collapses into one finding (not one per page). Per-URL lookups are pooled and capped at 150 (--crux-max-lookups <n>, or 0 for unlimited); if the cap forces origin-level fallback, or CrUX rate-limits (429) / rejects the key (401/403), pseolint says so rather than silently reporting "no data". The CrUX endpoint is a fixed Google host, so no external-authority dependency on your own content, consistent with pseolint's offline-runnable design.

GitHub Action

name: pSEO Lint
on: [pull_request]

jobs:
  audit:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
      - uses: actions/setup-node@v4
        with: { node-version: '20' }
      - run: npm run build
      - uses: ouranos-labs/[email protected]
        with:
          source: ./out
          threshold: 40

Posts a score summary as a PR comment and fails the check if score exceeds the threshold.

Pin to a release tag (@v0.8.0) or, if you prefer a moving ref that tracks the latest built bundle, ouranos-labs/pseolint/packages/action@action-v1. The tag form is the one listed on the GitHub Actions Marketplace: Marketplace only indexes an action.yml at the repository root, so /packages/action@… resolves the same action but is invisible to search there.

Outputs: risk, score (alias), verdict, pageCount, truncated, truncated-reason. When truncated is true, treat the numbers as lower bounds: see Partial coverage.

Fix rail: from audit to pull request

The AI orchestrator produces a fix manifest (validated patches). pseolint apply writes the deterministic ones (meta titles, H1s, robots.txt, sitemap.xml) straight into your source tree; generative or unmatched patches are demoted to a checklist for a human. --pr takes the next step: commit those edits to a tool-owned branch and open a PR.

# 1. Audit → manifest
pseolint orchestrate https://example.com --max-cost 3 --manifest-out manifest.json

# 2. Apply deterministic edits into your working tree (review the diff, commit yourself)
pseolint apply manifest.json

# 3. …or apply + commit + open a GitHub PR in one step
pseolint apply manifest.json --pr --token "$GITHUB_TOKEN"

Mapping (.pseolint/templates.json)

Audited routes don't know your source layout, so you map them once (route pattern → source file). Domain-level patches use the special robots.txt / sitemap.xml keys:

{
  "/listing/:slug": "app/listing/[slug]/page.tsx",
  "/category/:slug": "app/category/[slug]/page.tsx",
  "robots.txt": "public/robots.txt",
  "sitemap.xml": "app/sitemap.ts"
}

Route keys accept :seg / [seg] / * wildcards. A patch with no matching entry (or a literal that can't be found in an interpolated template like Best in ${city}) lands in the checklist (or the PR body) instead of silently corrupting source.

In CI

apply --pr uses git + one GitHub API call; no extra dependency. Give the workflow write permissions and let actions/checkout configure the push token:

name: pSEO fix PR
on: { workflow_dispatch: {} }

jobs:
  fix:
    runs-on: ubuntu-latest
    permissions: { contents: write, pull-requests: write }
    steps:
      - uses: actions/checkout@v4
      - uses: actions/setup-node@v4
        with: { node-version: '20' }
      - run: npm run build
      - run: npx pseolint orchestrate http://localhost:3000 --max-cost 3 --manifest-out manifest.json
        env: { ANTHROPIC_API_KEY: '${{ secrets.ANTHROPIC_API_KEY }}' }
      - run: npx pseolint apply manifest.json --pr
        env: { GITHUB_TOKEN: '${{ github.token }}' }

Re-running updates the same pseolint/fix-<domain> branch (force-with-lease, tool-owned branch only); it never spams new PRs. It no-ops cleanly when there's nothing deterministic to apply.

Output Formats

npx pseolint https://yoursite.com                  # Colored terminal (default)
npx pseolint https://yoursite.com --format json    # CI-friendly JSON
npx pseolint https://yoursite.com --format markdown # PR comments / docs
npx pseolint https://yoursite.com --format html    # Self-contained visual report

Monorepo

Development

bun install
bun run build
bun run test     # 1,203 tests across 126 files (core)

Roadmap

• AI-inferred template mapping: today apply --pr needs a hand-authored .pseolint/templates.json; infer route→source automatically.
• Closing blind spots: schema-content drift, outbound-link health, search-intent alignment. Every gap is tracked by impact tier in the blind-spot audit. (Core Web Vitals landed: lab LCP/CLS via --render, real-user field p75 + INP via --crux-api-key.)
• Web "Open PR" button: the fix rail runs from the CLI/Action today; a hosted one-click flow is deferred until the GitHub-App auth is justified.

Found a false positive or a missing check? Open an issue. Corpus-backed bug reports move the calibration.

Contributing

Issues and PRs welcome. See CONTRIBUTING.md for the dev loop, and skills/ if you want to teach an agent to design pass-first pages. If pseolint saved you a SpamBrain headache, a ⭐ helps others find it.

License

MIT (packages) / AGPL-3.0 (apps/web)