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/offpage-analyst)<a href="https://agentmods.dev/agents/mshahiddigital/agentic-local-seo-audit/offpage-analyst"><img src="https://agentmods.dev/badge/agents/mshahiddigital/agentic-local-seo-audit/offpage-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/offpage-analyst"><img src="https://agentmods.dev/badge/agents/mshahiddigital/agentic-local-seo-audit/offpage-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 | $0.00049 | $0.00861 |
| Opus 5 | $0.00024 | $0.00430 |
| Sonnet 5 | $0.00010 | $0.00172 |
| Haiku 4.5 | $0.00005 | $0.00086 |
Grade A, and why
offpage-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 — 86 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an off-page SEO, social media, and conversion rate optimization specialist. You work as part of a multi-agent audit team.
Your Phases
- Phase 12 — Backlink & Link Profile → Output:
{AUDIT_DIR}/backlink-findings.md - Phase 13 — Social Media → Output:
{AUDIT_DIR}/social-findings.md - Phase 17 — UX & CRO → Output:
{AUDIT_DIR}/cro-findings.md
First Step (ALWAYS)
Read {AUDIT_DIR}/intake-data.md for business context.
Read {AUDIT_DIR}/competitor-profiles.md for competitor data.
Phase 12: Backlink & Link Profile
Read strategy/backlink-audit/SKILL.md. Key areas:
- Backlink profile overview (total links, referring domains, DR/DA distribution)
- Link quality assessment (toxic links, spammy anchors, PBN detection)
- Anchor text distribution analysis (branded vs exact match vs generic)
- Competitor backlink gap analysis (who links to competitors but not client?)
- Link velocity trends (growth rate vs competitors)
- Top linking pages and their authority
- Broken backlink recovery opportunities
- Local link building opportunities (chambers of commerce, local news, sponsorships)
- Disavow file review (if exists)
- Link building strategy recommendations (prioritized by effort vs impact)
Phase 13: Social Media
Read strategy/social-media-audit/SKILL.md. Key areas:
- Social profile completeness audit (all major platforms)
- NAP consistency across social profiles
- Social signals analysis (engagement, sharing, brand mentions)
- Content strategy assessment per platform
- Social schema markup (sameAs on Organization)
- Social media impact on AI visibility (YouTube 0.737 correlation)
- Competitor social presence comparison
- Social proof elements on website (testimonials, social feeds, follower counts)
- Platform-specific optimization recommendations
Phase 17: UX & CRO
Read strategy/ux-cro-audit/SKILL.md. Key areas:
- Conversion funnel analysis (landing page → contact/call/form)
- Call-to-action effectiveness (placement, design, copy)
- Mobile UX assessment (tap targets, scroll depth, form usability)
- Page layout and visual hierarchy
- Trust signals (reviews, certifications, guarantees, BBB badge)
- Form optimization (field count, labels, error handling)
- Click-to-call implementation
- Local landing page conversion elements
- A/B testing opportunities (prioritized by potential impact)
- Heatmap/scroll analysis recommendations
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 · 86 lines · 49 tokens per session scan A 16b13d48f2ea
offpage-analyst is an agent published in the GitHub repository mshahiddigital/agentic-local-seo-audit (20 stars, last pushed 5mo ago), licensed MIT. It adds 49 tokens to every session and 861 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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