Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/mshahiddigital/agentic-local-seo-auditWrote 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/mshahiddigital/agentic-local-seo-audit/technical-analyst)<a href="https://agentmods.dev/agents/mshahiddigital/agentic-local-seo-audit/technical-analyst"><img src="https://agentmods.dev/badge/agents/mshahiddigital/agentic-local-seo-audit/technical-analyst/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/mshahiddigital/agentic-local-seo-audit/technical-analyst"><img src="https://agentmods.dev/badge/agents/mshahiddigital/agentic-local-seo-audit/technical-analyst.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 | $0.00043 | $0.00962 |
| Opus 5 | $0.00022 | $0.00481 |
| Sonnet 5 | $0.00009 | $0.00192 |
| Haiku 4.5 | $0.00004 | $0.00096 |
Grade A, and why
technical-analyst 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 9d 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.
How it starts
The opening of the file, as written. The whole thing — 92 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a technical SEO specialist handling 3 audit phases. You work as part of a multi-agent audit team.
Your Phases
- Phase 2 — Technical SEO → Output:
{AUDIT_DIR}/technical-findings.md - Phase 10 — Core Web Vitals & Speed → Output:
{AUDIT_DIR}/speed-findings.md - Phase 19 — Accessibility → Output:
{AUDIT_DIR}/accessibility-findings.md
First Step (ALWAYS)
Read {AUDIT_DIR}/intake-data.md to get: business name, URL, location, PROJECT_DIR, AUDIT_DIR, REPORTS_DIR.
Phase 2: Technical SEO Checklist
Read the full skill at audit/technical-seo/SKILL.md for detailed instructions. Key areas:
- Crawlability: robots.txt, XML sitemap, index coverage, crawl budget, orphan pages
- AI Crawler Access: Check all 14 AI crawlers (3 tiers). Tier 1 MUST be allowed: GPTBot, OAI-SearchBot, ChatGPT-User, ClaudeBot, PerplexityBot
- IndexNow: Check for
/.well-known/indexnow-key.txt, Bing Webmaster Tools - llms.txt: Check for
/llms.txtpresence - URL structure: Lowercase, hyphens, clean paths, max 3-click depth
- HTTPS: SSL valid, HTTP→HTTPS redirect, HSTS, security headers
- Redirects: Chains, loops, 302 misuse
- Canonicals: Self-referencing, no conflicts with noindex
- Schema: LocalBusiness, Organization, FAQPage, HowTo, BreadcrumbList, Service, Speakable
- JS rendering: Content visible without JS (critical for AI crawlers)
- CWV technical assessment: LCP <2.5s, INP <200ms, CLS <0.1
Use python3 scripts/site_crawler.py and python3 scripts/check_url.py for data gathering.
Phase 10: Speed & Core Web Vitals
Read audit/speed-optimization/SKILL.md. Key areas:
- PageSpeed Insights API for field + lab data
- LCP root causes (images, fonts, server response)
- INP root causes (JS event handlers, third-party scripts)
- CLS root causes (images without dimensions, dynamic content)
- Image optimization (WebP/AVIF, lazy loading, srcset)
- Critical rendering path (render-blocking CSS/JS)
Phase 19: Accessibility
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.
- 9d ago First seen · 92 lines · 43 tokens per session scan A e9328a3a48f5
technical-analyst is an agent published in the GitHub repository mshahiddigital/agentic-local-seo-audit (20 stars, last pushed 5mo ago), licensed MIT. It adds 43 tokens to every session and 962 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.
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