Cherry-picked from claude-seo (github.com/AgriciDaniel/claude-seo, MIT)
content_quality.py, rewritten to the lib/seo-data contract per BDR-070. The
Content Shape axis was 100% LLM judgement; this gives it a measured input.
fetch.sh content_quality (stdin or --file) → {filler_score, ai_pattern_score,
information_density, overall_quality, flags[], matches{}}. 100% deterministic:
QRG §4.6 filler list (26 phrases) + AI-pattern list (46) kept intact, regex
matching, no LLM. Stdlib only (argparse/json/re/sys/collections/typing).
Advisory, NOT a verdict — the point of the wiring. It never claims a page "is
AI-written" (LRN-131/133); flags are candidates for human review. geo-analyzer
STEP 8 Check 10 makes it a deterministic input that INFORMS checks 1-9, never
replaces them, never scored on its own. A low number is not an automatic
finding.
Detection proven both directions (a detector that always- or never-flags is
useless): filler+slop text → flags [filler, low-density], overall 34-49; clean
dense factual text (dates/EUR/percentages) → no flags, overall 90. Empty input →
degraded/empty_input, never zeros-as-a-result.
Verified: GATE 1 verifier CONFORME 10/10 (both directions exercised live, lists
diffed intact vs source, advisory language confirmed); GATE 2 self-scan clean
(only sink is read-only open() for --file); seo-data 190 → 210 pass, 0 fail;
full suite green; shellcheck + py_compile clean.
24 KiB
seo-data — GSC + CrUX data layer for /seo FULL audits
Small, isolated engine that gives the /seo skill real Google data instead of
guesses: Search Console (queries, positions, indexation) and CrUX
(Core Web Vitals field data — real users, not lab simulation). It knows
nothing about SEO scoring; it only turns Google APIs into normalized JSON.
The seo-analyzer agent consumes that JSON in STEP 4 (Core Web Vitals) and
the new "Performance GSC" subsection; the /seo skill selects the account
and property in STEP 0 of a FULL audit (not needed for LOCAL).
Multi-account by design: the token store is keyed by a user-chosen label, and
every call takes --account/--property explicitly. Two audits running at
the same time (two sites, two sessions) never share mutable state — nothing
is written to disk during an audit, only at make seo-connect.
Setup
One-time per Google account:
make seo-connect # from the claude-config repo
bash ~/.claude/lib/seo-data/connect.sh --label <label> # from ANY directory (venv must exist)
make seo-connect creates ~/.claude/.venv-seo-data/ (isolated venv, deps
pinned in requirements.txt), installs google-auth,
google-auth-oauthlib, requests, then delegates to connect.sh. The
wrapper sources ~/.claude/.env internally, prefers the venv python, and
runs connect.py: it opens a browser for OAuth consent and takes a
label (e.g. client-a) to key the account — pick a name, not an email,
since the store never stores or requests the account's email. Once the venv
exists, connect.sh alone connects further accounts from anywhere (the
/seo connect [label] skill verb uses exactly this path).
Before running it, set these 3 keys in ~/.claude/.env (the canonical
vault; link.sh only symlinks the repo's .env to it and warns with a
cp .env.example .env hint if it's missing — it never creates the vault
itself):
GOOGLE_OAUTH_CLIENT_ID=<your-client-id>.apps.googleusercontent.com
GOOGLE_OAUTH_CLIENT_SECRET=<your-client-secret>
CRUX_API_KEY=<your-crux-api-key>
GOOGLE_OAUTH_CLIENT_ID/GOOGLE_OAUTH_CLIENT_SECRET— OAuth2 "Desktop app" credentials from the Google Cloud Console (APIs & Services → Credentials). Shared across every account you connect; the OAuth scope requested ishttps://www.googleapis.com/auth/webmasters.readonlyonly — read-only Search Console, nothing can be modified or deleted via this token.CRUX_API_KEY— a Chrome UX Report API key (restrict it to CrUX + PageSpeed in the Console). Get one at https://developer.chrome.com/docs/crux/api. No OAuth involved: CrUX is public field data, gated by API key only, independent of any connected account.
make seo-connect is idempotent and rerunnable — connecting a second
account just runs it again with a different label; reusing an existing
label prompts to overwrite.
fetch.sh contract
lib/seo-data/fetch.sh is the one stable entrypoint analyzers call. It
sources ~/.claude/.env, prefers the isolated venv (falls back to system
python3 for stdlib-only paths), dispatches to google_seo.py or
tokenstore.py, and never prints a secret to stdout or stderr.
fetch.sh accounts
→ {"status":"ok","accounts":[{"label":"…","properties":[…],"granted_at":"…"}]} # [] if none connected
fetch.sh crux --url https://ex.com [--strategy mobile|desktop]
→ {"status":"ok","source":"crux","lcp_p75_ms":…,"inp_p75_ms":…,"cls_p75":…} # a missing metric omits its key
→ {"status":"degraded","reason":"no_crux_key"|"no_field_data"|"rate_limited"}
# a 404 on page-level data retries at origin-level before degrading
fetch.sh queries --account client-a --property sc-domain:ex.com [--days 90] [--dim query|page]
→ {"status":"ok","source":"gsc","dimension":"query","rows":[{"key":"…","clicks":…,"impressions":…,"ctr":…,"position":…}]}
→ {"status":"degraded","reason":"no_credentials"|"token_revoked"|"network_error"|"rate_limited"}
fetch.sh inspect --account client-a --property … --url https://ex.com/page
→ {"status":"ok","source":"gsc","indexed":true,"coverage":"…","last_crawl":"…",
"rich_results":{"verdict":"PASS|FAIL|NEUTRAL|VERDICT_UNSPECIFIED|ABSENT",
"types":[{"type":"FAQ","items":2,"errors":2,"warnings":1,
"issues":["Missing field 'acceptedAnswer'"]}]}}
→ {"status":"degraded","reason":"…"}
rich_results rides the SAME URL-Inspection response — Google already sends
it, `inspect` used to discard it. No extra call, quota or OAuth scope.
It is the only programmatic structured-data validation in the system.
• verdict PARTIAL is never emitted — the API reserves it as unused.
• verdict ABSENT is SYNTHETIC (not a Google enum): the API omits
richResultsResult entirely when it detects no rich results. Surfaced
as a value rather than a missing key, because a caller cannot tell an
absent key apart from a check that never ran. ABSENT = "none
detected", never "invalid".
• errors/warnings count issue INSTANCES; issues[] is deduped — the same
issueMessage repeats across every affected item.
fetch.sh cannibal --account client-a --property … [--days 90] [--rows 1000]
→ {"status":"ok","source":"gsc","days":90,"rows_scanned":1000,"capped":true,
"conflict_count":12,
"conflicts":[{"query":"plombier paris","pages":3,"total_impressions":2400,
"urls":[{"url":…,"clicks":…,"impressions":…,"position":…}]}]}
→ {"status":"degraded","reason":"…"} # no account → NOT auditable
Keyword cannibalisation from Google's own data: queries where 2+ of OUR
pages compete. Groups query+page rows; conflicts ranked by total
impressions, and within each the strongest page first. `capped:true` means
the row window was full — more conflicts exist past the cut, say so.
Same auth, same quota family, no new scope: the API always accepted several
dimensions at once, this engine only ever asked for one.
• NOT the 30/70 duplication rule. This is a SERP fact Google measured.
30/70 is content similarity, which has no data source here — doing it
naively (compare two same-template pages without stripping nav/footer)
returns ~95% similar for every site, a confident false positive. It stays
an LLM judgement, labelled as one.
• `queries` now takes `--dim query,page` (comma-separated) and `--rows`.
Rows gained a `keys` list; `key` stays as keys[0], so the single-dim
consumer is untouched.
fetch.sh sitemap --url https://ex.com/sitemap.xml
→ {"status":"ok","source":"sitemap","index":false,"count":86,"dropped":0,
"urls":["https://ex.com/", …]}
→ {"status":"ok","index":true,"children_total":4,"children_read":4,
"children_failed":0,"count":312,…} # <sitemapindex>, one level deep
→ {"status":"degraded","reason":"fetch_failed"|"parse_failed"|"no_urls"
|"unsafe_xml_dtd"}
No auth, no Google, no venv: stdlib only (urllib + xml.etree + gzip).
Gives STEP 9's COVERAGE line the denominator it was told to print and never
had, and STEP 5 a real sampling frame. Dedupes, strips whitespace, handles
.xml.gz. Caps: 50 children of an index, 50k URLs, 20 MB read — each cut is
REPORTED (children_skipped / truncated), never silent.
• NOT a security boundary. urllib fetches these, so nothing here reaches a
shell. The CONSUMER interpolates them into curl, so seo-analyzer runs
lib/url-guard.sh at the point of use — same contract as the sameAs check.
A second copy of the guard here would only drift.
• `unsafe_xml_dtd`: a sitemap NEVER has a DTD (sitemaps.org is <?xml?> then
<urlset xmlns=>). Any doctype/entity is refused BEFORE parsing. xml.etree
does not expand external entities, but it IS billion-laughs-vulnerable —
1 KB expands to gigabytes, and the 20 MB read ceiling bounds the input,
not the expansion. Refusing the construct beats depending on parser
internals AND keeps this stdlib-only; defusedxml would drag in a venv for
a document type that has no legitimate DTD.
fetch.sh rendercheck --url https://ex.com/
→ {"status":"ok","verdict":"server-rendered"|"client-rendered"|"partial",
"body_text_chars":7650,"h1_in_html":1,"jsonld_in_html":9,
"meta_description_in_html":true,"html_bytes":132447,
"warning":"…"} # warning only when not server-rendered
R2, the honest half of the SPA call. seo-analyzer has always recorded
`RENDERING: SSR/SSG/SPA` and never acted on it; this is the signal it acts
on. Verdict comes from what the server SENT — package.json cannot tell a
React SPA from a Next.js SSR app.
• client-rendered → the agent REFUSES to score On-page (N/A, not zero: a
zero says "your on-page is bad", N/A says "we could not see it"). Every
curl-based meta/H1/JSON-LD check would report "missing" against a site
that is fine once hydrated — false findings, and a bundle that "fixes"
tags which already exist.
• Does NOT render JS. No Playwright, no Chromium, no venv. Refusing IS the
finding.
• Script/style text is not page text: measured 7 chars on a React shell
whose inline window.__INITIAL_STATE__ is large. Without that, a 200 KB
bundle reads as a rich page.
• Measured 2026-07-17: zenquality 7650 chars/1 h1/9 jsonld and
lavageangels356 13973/1/1 → server-rendered; a Vite shell → 7/0/0.
fetch.sh linkgraph --url https://ex.com/sitemap.xml [--max 500]
→ {"status":"ok","source":"linkgraph","pages_crawled":86,"pages_failed":0,
"total_internal_links":2015,"capped":false,"max_depth":2,
"orphans":[…],"beyond_3_clicks":[…],"unreachable":[…]}
→ {"status":"ok",…,"orphans_withheld":true,"reason_withheld":"crawl incomplete…"}
→ {"status":"degraded","reason":"no_links_in_html"|"no_pages_fetched"|…}
Answers seo-analyzer.md:613 ("reachable within 3 clicks?") and :616 ("orphan
pages?") — asked since forever, never computed. Stdlib only (urllib +
html.parser + urljoin), no auth. Measured: 24 pages in 2.7s, 86 in 3.8s.
• EXHAUSTIVE OR NOTHING. Orphans cannot be sampled: proving no inbound
link means having read every other page. If the crawl is capped or any
page failed, orphans are WITHHELD, never truncated — a false orphan
sends a client fixing what is not broken.
• no_links_in_html = a JS-rendered site, not a link-less one. Every page
would read as orphaned, so it REFUSES rather than report that. Does not
render JS by design (see the R1/R2 arbitration).
• Filters what a link graph must never hold: assets (seen live:
/css/main.css?v=1778157313), #anchors, mailto:/tel:/javascript:, other
hosts. Normalises the trailing slash so /blog and /blog/ are one node
rather than a phantom orphan pair.
• Mock is pages.json ({url: html}), not a single page.html: one fixture
cannot express a graph — every node would carry identical links.
fetch.sh score --findings <path.json | ->
→ {"status":"ok","axes":{"technical":{"score_20":17.8,"weight":0.2,
"weight_renormalised":0.2857,"findings":2}},
"na":["off-page","on-page"],"weights_renormalised":true,"global_20":17.6}
→ {"status":"error","reason":"unknown severity: 'bogus'"|"bad_findings_json"}
I7. /harden has a real scale (SKILL.md:435: -15/-8/-3/-1, clamp [0,100]);
/seo had none, so every axis was FELT and two runs over identical code could
disagree — while /client-handover gates on 17/20. Same scale here, /5 into
/20, one vocabulary across the family.
• The split: WHICH findings exist and how severe each is stays the LLM's
judgement. The addition is not. Same findings in, same score out.
• affected/sampled shift severity ONE step: >=50% of the sample escalates,
a single page de-escalates. A defect on 1 of 12 pages is not the defect
on 12 of 12.
• status:"na" → axis EXCLUDED, remaining weights renormalised. This is
R2's rule (client-rendered on-page) and I1's (unauditable off-page),
computed rather than done by hand. N/A is not a zero, and the engine
will not let it act like one.
• Malformed input is an error, never a silently wrong number — unlike the
fetch verbs, a degrade here would mean bad input, not a network fact.
fetch.sh schema_gen <reservation|order|discussion|profile> [flags] [--script-tag]
→ {"status":"ok","source":"schema_gen","type":"<@type>","jsonld":{…}}
→ {"status":"error","reason":"bad_usage"} # a REQUIRED flag omitted
→ {"status":"degraded","reason":"…"} # a required flag given, empty
fetch.sh schema_gen reservation --provider "Marea NYC" \
--start 2026-06-04T19:30:00-04:00 --party-size 4
fetch.sh schema_gen order --merchant "Acme Pizza" --order-url https://acme.example/order
fetch.sh schema_gen discussion --headline "…" --author "Sara Park" \
--url https://forum.example.com/t/123 --date 2026-05-12T14:00:00Z
fetch.sh schema_gen profile --name "Daniel Agrici" --url https://agricidaniel.com/about \
--same-as https://github.com/AgriciDaniel --knows-about "SEO" "Schema markup"
Adapted from claude-seo's `schema_generate.py` (MIT) into this contract.
Our system only AUDITS existing markup elsewhere; this is the one verb
that GENERATES it — deterministic JSON-LD skeletons for the four v2
high-leverage Schema.org types, so geo-analyzer's G2 batch stops
hand-writing markup by hand. It only generates STRUCTURE: unknown field
VALUES are the caller's job, `[À COMPLÉTER]` for anything unconfirmed —
this verb never invents a sameAs, an email, or a business name.
• Stdlib only, no network, no auth — runs even without the venv.
• `--script-tag` wraps the cleaned jsonld in
`<script type="application/ld+json">…</script>` under a `script` key,
still inside the `ok` envelope. It must be given AFTER the type
(`schema_gen reservation … --script-tag`, not before) — argparse
subcommand flags only parse after their subcommand.
• Never emits a JSON `null`: fields left unset are omitted from the
`jsonld` object entirely rather than serialised as `null`.
• A REQUIRED flag omitted → `{"status":"error","reason":"bad_usage"}`,
exit 2 (bad usage, like every other verb). A required flag GIVEN but
empty (argparse cannot catch that) → `{"status":"degraded",...}`,
exit 0 — fail-open, never a traceback.
fetch.sh content_quality [--file <path.txt>] < text_on_stdin
→ {"status":"ok","source":"content_quality","filler_score":0,"ai_pattern_score":0,
"information_density":1.0,"overall_quality":90,"flags":[],
"matches":{"filler":[],"ai_patterns":[]}}
→ {"status":"degraded","reason":"empty_input"|"<file error>"}
fetch.sh content_quality --file article.txt
printf '%s' "$BODY_TEXT" | fetch.sh content_quality
Adapted from claude-seo's `content_quality.py` (MIT) into this contract.
100% deterministic — regex/word-lists (QRG §4.6 filler phrases + a
Wikipedia "AI Cleanup" catalogue of LLM-typical phrasings, CC BY-SA 4.0),
no LLM call, no network. Reads the text to score from `--file <path>` or,
when `--file` is `-` or omitted, from stdin — the same idiom `score.py`
uses for `--findings`.
• **ADVISORY, NOT A VERDICT.** The output never claims "this text is
AI-written" — modern generative tools can pass every heuristic here,
and human writers use some of these phrases too. `flags` are
candidates for HUMAN REVIEW, never an automatic finding. geo-analyzer
STEP 8 (Content Shape for AI) treats `overall_quality`/`flags` as ONE
measured input that INFORMS the axis; the axis itself stays an LLM
judgement (30/70, Definition Lead), never replaced by this score.
• `filler_score`/`ai_pattern_score` (0-100, higher = worse) count
phrase-list hits scaled per 1000 tokens; `information_density`
(0.0-1.0) is entities + numbers per 100 tokens; `overall_quality`
(0-100, higher is better) is the weighted composite (also folds in a
bigram-repetition penalty even though that score isn't itself a
top-level field). `flags` fires at fixed thresholds: `filler`,
`ai-patterns`, `low-density`, `repetitive`.
• Stdlib only (argparse/json/re/sys/collections/typing) — runs even
without the venv. Empty/whitespace-only input degrades rather than
returning a false zero-value "ok": an empty analysis is not a result.
• This is filler/AI-pattern SHAPE, not fact-checking — a text can be
dense and well-cited yet still wrong; that stays a human/LLM call.
fetch.sh drift --url https://ex.com/sitemap.xml [--max 500]
→ {"status":"ok","baseline":true,"captured":"…","pages":24,"store":"…"}
→ {"status":"ok","baseline":false,"since":"…","gone":[…],"new":[…],
"regressions":[{"url":…,"field":"canonical","was":"…","now":null}],
"changes":[{"url":…,"field":"title","was":"…","now":"…"}]}
On-page drift between audits. seo-analyzer.md:1365 keeps only "date + score
+ key changes" as PROSE the LLM writes about its own previous prose: lossy,
unreproducible, machine-uncomparable. So "the redesign silently dropped 40
canonicals" stays invisible. This snapshots title/description/canonical/
robots/h1_count/jsonld_types per URL and diffs them.
• NOT rank tracking (the common misread of this feature elsewhere).
Positions come from GSC `queries`. This is regression detection.
• Runs over the WHOLE sitemap, never a sample: a drift over a sample that
changes between runs compares nothing.
• LOSING a signal = regression. CHANGING one = change, possibly intended —
the agent judges that, the engine only says which kind it is.
• Store: ~/.claude/seo-data/drift/<host>.json, 0700, written via
os.replace — never a half-written baseline. Corrupt store → treated as
a first run rather than crashing the audit.
fetch.sh forget --label client-a
→ {"status":"ok","removed":true|false} # false = label wasn't in the store
fetch.sh forget --all
→ {"status":"ok","cleared":<n>} # n = accounts removed
Rules that hold for every subcommand:
- JSON always on stdout, never empty. Even an unexpected error (HTTP
403/5xx, timeout, DNS failure) prints
{"status":"degraded","reason":"unexpected_error"}— never a raw traceback. statusis"ok"or"degraded"on exit 0;"error"on exit 2. Analyzers branch on this field;"error"only shows up on bad usage,reasonis informational otherwise.- Exit code 0 on
okand ondegraded. The engine never fails the process just because Google data isn't available — that's a normal, expected outcome the analyzer handles by falling back. Exit code 2 is reserved for bad usage: unknown subcommand, missing required flag, invalid argument — those paths emit{"status":"error",...}instead. --storeis accepted uniformly by every subcommand for consistentfetch.shdispatch, even thoughcruxignores it (CrUX needs no account).- Never prints a secret. No env var, refresh token, or access token ever reaches stdout or stderr, including in error paths.
Two env vars exist for testing, never for normal use:
SEO_DATA_ENV_FILE overrides which env file is sourced (tests point it at
/dev/null so a real ~/.claude/.env on the machine can never leak into a
test run), and SEO_DATA_DEBUG=1 re-enables stderr for local debugging
(stderr is suppressed by default so library warnings can't leak a secret
into an agent's context).
Token store
~/.claude/seo-data/tokens.json — refresh tokens, keyed by the label chosen
at make seo-connect, one entry per connected account:
{
"version": 1,
"accounts": {
"client-a": {
"refresh_token": "<opaque>",
"scopes": ["https://www.googleapis.com/auth/webmasters.readonly"],
"granted_at": "2026-07-09T12:00:00+00:00",
"properties": ["sc-domain:site-a.com", "https://www.site-a.com/"]
}
}
}
Security posture:
- File
0600, directory0700.tokenstore.save_accountre-asserts both permissions on every write. - Written only at
connecttime, atomically.tmp→fsync→os.replace(atomic rename), under an exclusivefcntllock, so two simultaneousmake seo-connectruns can't corrupt the file. Audits never write to this file — access tokens are exchanged in memory and never persisted, so two audits running concurrently never contend on it. - Keyed by label, not email. Identifying accounts by email would
require widening the OAuth scope just for identification; the label the
user picks at connect time is sufficient and keeps the scope at
webmasters.readonlyonly (least privilege). - Refresh tokens are redacted from
list.fetch.sh accounts(andtokenstore.py list) return label, properties, andgranted_atonly — therefresh_tokenfield is intentionally never included in that output. - Allowlisted in gitleaks. The store lives under
~/.claude/, outside this repo, so it's never committed directly — butmake scan-secretsalso sweeps~/.claudefor stray copies of secrets..gitleaks.tomlhas an explicit[allowlist].pathsentry for(^|/)\.claude/seo-data/tokens\.json$, the same treatment~/.claude/.envalready gets, so a legitimate local secret store doesn't drown real findings in false positives. - Also gitignored (
.venv-seo-data/andseo-data/tokens.jsonin.gitignore) as a second, belt-and-suspenders guard in case a relative path ever put either under the repo tree. - Removal is local-only.
fetch.sh forget --label <x>/--all(the/seo forgetskill verb) deletes the stored refresh token — it does NOT revoke the OAuth grant at Google's end. For a real revocation, visit https://myaccount.google.com/permissions with the account concerned and remove the app's access; the deleted local token then becomes useless everywhere, including to anyone who copied it beforehand.
Graceful degradation
Missing API key, no connected account, or a revoked/expired token is a normal outcome, not a failure:
- No
CRUX_API_KEY→cruxreturns{"status":"degraded","reason":"no_crux_key"}. - No account connected, or the store has no refresh token for the given
--account→queries/inspectreturn{"status":"degraded","reason":"no_credentials"}. - Refresh token revoked at Google's end →
{"status":"degraded","reason":"token_revoked"}(a transient network blip during refresh is classified"network_error"instead, so a flaky connection never forces the user back through OAuth). - Rate limited (HTTP 429) on any Google API →
{"status":"degraded","reason":"rate_limited"}.
In every case: exit code 0, valid JSON on stdout, no crash. The /seo
FULL audit continues on the anonymous PageSpeed API (lab data) instead of
CrUX field data, and the report surfaces the fix as a user action:
make seo-connect. doctor.sh also flags both non-fatally as WARN: a
missing CRUX_API_KEY warns on its own, while no connected Google account
is the one that names make seo-connect.
Testing
make test
# or, to run only this engine's suite:
bash lib/seo-data/seo-data.test.sh
The suite is network-free: google_seo.py reads fixtures from
lib/seo-data/fixtures/ (crux_mobile.json, gsc_queries.json,
gsc_inspect.json) whenever SEO_DATA_MOCK_DIR is set, instead of calling
Google's APIs. Degradation paths run with real env vars unset (env -u CRUX_API_KEY, env -u SEO_DATA_MOCK_DIR) to exercise the no-key/no-creds
branches deterministically. Every fetch.sh invocation in the tests also
sets SEO_DATA_ENV_FILE=/dev/null so a machine with a live
~/.claude/.env never lets real credentials leak into a test run.