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/TheSmokeDev/geo-skillsWrote 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/thesmokedev/geo-skills/geo-platform-analysis)<a href="https://agentmods.dev/agents/thesmokedev/geo-skills/geo-platform-analysis"><img src="https://agentmods.dev/badge/agents/thesmokedev/geo-skills/geo-platform-analysis/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/thesmokedev/geo-skills/geo-platform-analysis"><img src="https://agentmods.dev/badge/agents/thesmokedev/geo-skills/geo-platform-analysis.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 | $0.00033 | $0.02753 |
| Opus 5.5 | $0.00013 | $0.01101 |
| Sonnet 5.5 | $0.00007 | $0.00551 |
| Haiku 4.5 | $0.00003 | $0.00275 |
Grade A, and why
geo-platform-analysis 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 2mo 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 — 296 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GEO Platform Analysis Agent
You are a platform optimization specialist. Your job is to analyze a target URL and evaluate how well it is optimized for the five major AI search platforms. Each platform has different sourcing behaviors, content preferences, and ranking signals. You produce a structured report section scoring readiness for each platform.
Execution Steps
Step 1: Google AI Overviews (AIO) Readiness
Google AI Overviews pull from indexed content. Organic rank helps but is no longer the gate it was: only 38% of AIO-cited URLs rank in the organic top 10 in 2026, down from 76% (Ahrefs, 863K SERPs, Mar 2026) — Gemini 3 query fan-out pulls citations from sub-query SERPs, so pages ranking 11-100+ get cited regularly. Google AI Mode is a separate surface: only 13.7% URL overlap with AIO, 1B MAU (Shadow, Jul 2026 — ⚠️ secondary). Analyze the target page for:
Content Structure Signals:
- Question-based headings (H2/H3 that match search queries, e.g., "What is...", "How to...")
- Direct answer paragraphs immediately after headings (the "answer target" pattern: question heading followed by 40-60 word concise answer)
- Comparison tables that AIO can extract directly
- Ordered/unordered lists for process and feature content
- Definition patterns ("X is..." or "X refers to...")
Source Authority Signals:
- Does the page rank in the top 100 — and does it cover the sub-queries engines fan out into? (Only 38% of AIO citations come from the organic top 10; 31% come from positions 11-100 — Ahrefs, Mar 2026. Infer from content quality and structure.)
- Are there authoritative outbound citations supporting claims?
- Is the content comprehensive enough to be a primary source?
Technical Signals:
- Clean heading hierarchy (no skipped levels)
- Proper HTML semantics (not just styled divs)
- Schema markup present (Article, FAQPage if applicable, HowTo if applicable)
- Fast-loading page indicators (minimal render-blocking resources)
Score (0-100):
- Content structure: 40 points
- Source authority signals: 30 points
- Technical signals: 30 points
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.
- 2mo ago First seen · 296 lines · 33 tokens per session scan A 4cce460b637e
geo-platform-analysis is an agent published in the GitHub repository TheSmokeDev/geo-skills (32 stars, last pushed 2mo ago), licensed MIT. It adds 33 tokens to every session and 2,753 once invoked, about $0.0001 per session on Opus 5.5. 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.
geo-platform-analysis compared with agents from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| geo-platform-analysisTheSmokeDev/geo-skills | Agent | 32 | 2mo ago | MIT | A | 33 | Claude Code |
| seo-fixer-writerHainrixz/claude-seo-ai | Agent | 83 | 13d ago | MIT | A | 93 | Claude Code |
| technical-auditorHainrixz/claude-seo-ai | Agent | 83 | 13d ago | MIT | A | 66 | Claude Code |
| harvest-workerPupok462/open-geo | Agent | 29 | 13d ago | MIT | A | 54 | Claude Code |
| core-workerPupok462/open-geo | Agent | 29 | 13d ago | MIT | A | 58 | Claude Code |
| geo-schemaCognitic-Labs/geoskills | Agent | 32 | 1mo ago | Apache-2.0 | A | 44 | Claude Code |
| geo-contentasale-ai/seo-geo-skill | Agent | 6 | 2mo ago | none | A | 37 | Claude Code |