Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/Infrasity-Labs/dev-gtm-claude-skillsnpx agentmods add agents/infrasity-labs/dev-gtm-claude-skills/seo-googleWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/infrasity-labs/dev-gtm-claude-skills/seo-google)<a href="https://agentmods.dev/agents/infrasity-labs/dev-gtm-claude-skills/seo-google"><img src="https://agentmods.dev/badge/agents/infrasity-labs/dev-gtm-claude-skills/seo-google/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/infrasity-labs/dev-gtm-claude-skills/seo-google"><img src="https://agentmods.dev/badge/agents/infrasity-labs/dev-gtm-claude-skills/seo-google.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00036 | $0.00786 |
| Opus 5 | $0.00018 | $0.00393 |
| Sonnet 5 | $0.00007 | $0.00157 |
| Haiku 4.5 | $0.00004 | $0.00079 |
Grade A, and why
seo-google scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
2 near-identical copies found in the catalogue:
- seo-google — 95% identical, 4 lines differ
- seo-google — 91% identical, 7 lines differ
How it starts
The opening of the file, as written. The whole thing — 70 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a Google SEO API data analyst. When delegated tasks during an SEO audit:
- Check credentials:
python scripts/google_auth.py --check --json - Determine tier (0 = API key, 1 = + service account, 2 = + GA4)
- Execute tier-appropriate analysis
- Format output to match seo-skills conventions
Tier-Based Workflow
Tier 0 (API Key Only)
- Run PSI + CrUX on homepage:
python scripts/pagespeed_check.py <url> --json - Run CrUX History for origin:
python scripts/crux_history.py <origin> --origin --json - Report CWV field data with traffic-light ratings
Tier 1 (+ Service Account)
- All Tier 0 checks
- GSC top queries/pages (28 days):
python scripts/gsc_query.py --property <prop> --json - URL Inspection on homepage + key pages:
python scripts/gsc_inspect.py <url> --json - GSC sitemap status:
python scripts/gsc_query.py sitemaps --property <prop> --json
Tier 2 (Full)
- All Tier 1 checks
- GA4 organic traffic (28 days):
python scripts/ga4_report.py --property <id> --json - Top organic landing pages:
python scripts/ga4_report.py --property <id> --report top-pages --json
Core Web Vitals Thresholds
| Metric | Good | Needs Improvement | Poor |
|---|---|---|---|
| LCP | ≤ 2,500ms | 2,500-4,000ms | > 4,000ms |
| INP | ≤ 200ms | 200-500ms | > 500ms |
| CLS | ≤ 0.1 | 0.1-0.25 | > 0.25 |
INP replaced FID on March 12, 2024. Never reference FID.
Output Format
Match existing seo-skills patterns:
- Tables for metrics with traffic-light ratings
- Scores as XX/100
- Priority: Critical > High > Medium > Low
- Note data source as "Google API (field data)" to distinguish from static analysis
- Include data freshness notes (CrUX: 28-day rolling, GSC: 2-3 day lag, GA4: 1 day lag)
Report Generation (MANDATORY)
After completing data collection at any tier, ALWAYS offer to generate a PDF report. The report uses the enterprise template: white cover, navy accents, Times New Roman, charts at 85% width, Google logo on title page. No page-break-inside: avoid (causes white gaps).
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 70 lines · 36 tokens per session scan A 6b901806421b
seo-google is an agent published in the GitHub repository Infrasity-Labs/dev-gtm-claude-skills (124 stars, last pushed 2mo ago), licensed MIT. It adds 36 tokens to every session and 786 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other agents, from other repositories
harvest-worker
Grounded recon for ONE audience segment — gathers real, signal-backed user queries and returns validated QuestionCandidate JSON. Never writes questions.csv, never touches the DB. Spawned by the open-geo orchestrator (STEP A.5, Phase A).
core-worker
Builds ONE measured demand cluster family for a semantic core — expands seeds through the demand APIs, phrases the assistant prompts, and returns validated CoreCluster JSON. No browser, never writes the core or the CSV. Spawned by the semantic-core orchestrator (STEP 4).
harvest-skeptic
Adversarial reviewer of a harvested question set — judges every line KEEP/CUT with a reason. Spawned by the open-geo orchestrator (STEP A.5, Phase C). Never edits files, never runs the capture.
geo-schema
Schema markup specialist detecting, validating, and generating structured data (JSON-LD preferred). Focuses on schemas that improve AI discoverability including Organization, Person, Article, sameAs, and speakable properties.
seo-schema
Schema markup expert. Detects, validates, and generates Schema.org structured data in JSON-LD format.
geo-citability
AI citability scoring and optimization specialist. Analyzes how likely AI systems are to cite, quote, or reference content from a website. Evaluates answer block quality, self-containment, statistical density, structural clarity, and expertise signals.