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.
npx skills add TheSmokeDev/geo-skills --skill geo-prospectgit 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/skills/thesmokedev/geo-skills/geo-prospect)<a href="https://agentmods.dev/skills/thesmokedev/geo-skills/geo-prospect"><img src="https://agentmods.dev/badge/skills/thesmokedev/geo-skills/geo-prospect/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/skills/thesmokedev/geo-skills/geo-prospect"><img src="https://agentmods.dev/badge/skills/thesmokedev/geo-skills/geo-prospect.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 | $0.00087 | $0.01734 |
| Opus 5 | $0.00044 | $0.00867 |
| Sonnet 5 | $0.00017 | $0.00347 |
| Haiku 4.5 | $0.00009 | $0.00173 |
Grade A, and why
geo-prospect 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.
This is a copy
100% identical to geo-prospect — 5 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 195 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GEO Prospect Manager
Purpose
Manage GEO agency prospects and clients through the full sales lifecycle.
All data is stored in ~/.geo-prospects/prospects.json (persistent across sessions).
Commands
| Command | What It Does |
|---|---|
/geo prospect new <domain> |
Create new prospect (interactive prompts) |
/geo prospect list |
Show all prospects with pipeline status |
/geo prospect list <status> |
Filter: lead, qualified, proposal, won, lost |
/geo prospect show <id-or-domain> |
Full prospect detail with history |
/geo prospect audit <id-or-domain> |
Run quick GEO audit and save to prospect record |
/geo prospect note <id-or-domain> "<text>" |
Add interaction note with timestamp |
/geo prospect status <id-or-domain> <new-status> |
Move through pipeline |
/geo prospect won <id-or-domain> <monthly-value> |
Mark as won, set contract value |
/geo prospect lost <id-or-domain> "<reason>" |
Mark as lost with reason |
/geo prospect pipeline |
Visual pipeline summary with revenue forecast |
Data Structure
Each prospect is stored as a JSON record:
{
"id": "PRO-001",
"company": "Electron Srl",
"domain": "electron-srl.com",
"contact_email": "[email protected]",
"contact_name": "",
"industry": "Educational Equipment Manufacturing",
"country": "Italy",
"status": "qualified",
"geo_score": 32,
"audit_date": "2026-03-12",
"audit_file": "~/.geo-prospects/audits/electron-srl.com-2026-03-12.md",
"proposal_file": "~/.geo-prospects/proposals/electron-srl.com-proposal.md",
"monthly_value": 0,
"contract_start": null,
"contract_months": 0,
"notes": [
{
"date": "2026-03-12",
"text": "Initial GEO quick scan. Score 32/100 - Critical tier. Strong candidate for GEO services."
}
],
"created_at": "2026-03-12",
"updated_at": "2026-03-12"
}
Orchestration Instructions
/geo prospect new <domain>
- Check if
~/.geo-prospects/prospects.jsonexists, create if not (empty array) - Auto-detect company name from domain (e.g.,
electron-srl.com→Electron Srl) - Assign next sequential ID:
PRO-001,PRO-002, etc. - Ask user for:
- Contact name (optional)
- Contact email
- Monthly contract value estimate (optional)
- Set status to
lead - Save to JSON file
- Suggest next step: "Run
/geo prospect audit electron-srl.comto score this prospect"
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 · 195 lines · 87 tokens per session scan A 50cbf2fff70e
geo-prospect is a skill published in the GitHub repository TheSmokeDev/geo-skills (22 stars, last pushed 9d ago), licensed MIT. It adds 87 tokens to every session and 1,734 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to geo-prospect, differing in 5 lines, and is treated as a copy.
Other skills, from other repositories
orangeo-ai-visibility-skill
Audit brand AI visibility readiness and prepare OranGEO-style GEO, AEO, LLM SEO, and AI search optimization action plans. Use when asked for a Claude Code skill, Codex skill, GEO skill, generative engine optimization skill, answer engine optimization skill, AI visibility audit, AI search visibility checker, llms.txt…
ganhuo-geo-engineer
Use this Skill when the user provides an existing article, product page, tutorial, FAQ, or knowledge note and wants to rebuild it into a GEO or AI-search-friendly content asset. Use it for old-content refresh, citation-readiness improvement, answer-first restructuring, GEO upgrades, and Ganhuo AI content workflows. Do…
ai-answer-trace
Ask Claude, ChatGPT, and Gemini a question and capture the full evidence trail behind each answer: the search queries each engine ran, the pages it retrieved, and the sources it cited. The raw material of GEO measurement. Needs AI engine API keys, not an Xpoz account.
geo-visibility-check
One-shot GEO audit: does your brand appear in Claude, ChatGPT, and Gemini answers for the buyer questions that matter? Runs a prompt panel through the engines with citation tracing and reports per-prompt verdicts, who wins instead, and which sources the answers come from.
crazyseo
Measure and fix whether AI assistants (ChatGPT, Gemini, Perplexity) recommend a website. Use when someone asks "am I visible in AI search", "does ChatGPT recommend us", "why doesn't AI mention my brand", "GEO/AEO audit", "AI SEO", "llms.txt", "is my site readable by AI crawlers", or wants to know which sources AI…
xerj-code
Reference-coding with XERJ. Clone the libraries that already solved your problem, index them locally, and retrieve the exact implementation before writing code — so the agent reads passages instead of re-deriving algorithms across retry loops. Use when starting a task in an unfamiliar API, porting an algorithm, or…