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 The-AI-Directory-Company/agents-and-skills --skill discovery-gseogit clone --depth 1 https://github.com/The-AI-Directory-Company/agents-and-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/the-ai-directory-company/agents-and-skills/discovery-gseo)<a href="https://agentmods.dev/skills/the-ai-directory-company/agents-and-skills/discovery-gseo"><img src="https://agentmods.dev/badge/skills/the-ai-directory-company/agents-and-skills/discovery-gseo/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/the-ai-directory-company/agents-and-skills/discovery-gseo"><img src="https://agentmods.dev/badge/skills/the-ai-directory-company/agents-and-skills/discovery-gseo.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 | $0.00057 | $0.07470 |
| Opus 5 | $0.00028 | $0.03735 |
| Sonnet 5 | $0.00011 | $0.01494 |
| Haiku 4.5 | $0.00006 | $0.00747 |
Grade A, and why
discovery-gseo 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 8d 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 — 448 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Discovery GSEO
Discovery GSEO is the upstream layer that determines what to build before the execution skills take over. Without good discovery, all downstream SEO and GEO effort is wasted — targeting the wrong keywords, creating content for topics nobody searches for, missing opportunities competitors are already winning.
This is skill 0 of 5 in the SGEO series: discovery-gseo > technical-sgeo > on-page-sgeo > content-sgeo > off-page-sgeo.
The output of this skill is a prioritized content plan — keywords mapped to pages, scored on 4 dimensions (including GEO opportunity), ordered by impact. Everything else in the SGEO pipeline flows from this plan.
Before you start
Gather the following from the user. If anything is missing, ask before proceeding:
- What is your business/product? (Product category, target market, value proposition)
- What is your site URL? (Existing site for quick win analysis, or "new site" if starting from scratch)
- Who are your known competitors? (3-5 domains — business competitors AND SEO competitors)
- What is your current SEO status? (Brand new / some content / established — determines whether Phase 10 is applicable)
- Do you have Google Search Console access? (Critical for Phase 10 quick wins)
- What is the target country/region? (For localized SERP analysis and volume data)
- What is your budget for tools? (None / small / moderate / significant — determines which paid tool paths are available)
- How important is AI visibility? (Determines weight of GEO scoring in prioritization — low / medium / high)
If the user says "I just want to find keywords," push back: "Keywords without intent classification, competitor validation, and prioritization scoring produce a random list, not a strategy. Which phase do you want to start from?"
Tool discovery
Before gathering project details, confirm which tools are available. Ask the user directly — do not assume access to any external service.
What ships with it
18 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- references/browser-automation-guide.md 15 KB
- references/community-listening.md 7.9 KB
- references/competitor-intelligence.md 8.3 KB
- references/evaluation-and-scoring.md 16 KB
- references/keyword-expansion.md 12 KB
- references/seed-generation.md 8.1 KB
- scripts/analyze-serp-live.py 8.9 KB runs code
- scripts/build-topic-clusters.py 7.6 KB runs code
- scripts/classify-intent-live.py 8.0 KB runs code
- scripts/competitor-gap-analysis.py 5.3 KB runs code
- scripts/evaluate-keywords.py 7.1 KB runs code
- scripts/extract-paa.py 6.4 KB runs code
- scripts/find-quick-wins.py 7.0 KB runs code
- scripts/harvest-autocomplete.py 7.9 KB runs code
- scripts/prioritize-opportunities.py 9.2 KB runs code
- scripts/probe-ai-discovery.py 5.5 KB runs code
- scripts/scrape-community-keywords.py 6.8 KB runs code
- scripts/scrape-related-searches.py 5.9 KB runs code
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.
- 8d ago First seen · 448 lines · 57 tokens per session scan A f0c71b04a9fa
discovery-gseo is a skill published in the GitHub repository The-AI-Directory-Company/agents-and-skills (2 stars, last pushed 5mo ago), licensed MIT. It adds 57 tokens to every session and 7,470 once invoked, about $0.0003 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 2026-09-03.
Other skills, from other repositories
writing-workflow-skills
Use when adding a new workflow skill to pi-thinkrail-workflow, changing an existing workflow skill's role, trigger, handoff, or structure, or checking a workflow skill against the workflow system's rules. Not for authoring general-purpose skills outside this package.
case-interview-practice
Interactive consulting case interview practice with structured frameworks, feedback mechanisms, and progressive difficulty. Use when preparing for management consulting interviews, case competitions, or business problem-solving exercises.
i18n-localization
Internationalization and localization for global applications. Use when adding multi-language support, handling regional formats, or preparing apps for global markets.
electron-desktop
Desktop application development with Electron for Windows, macOS, and Linux. Use when building cross-platform desktop apps, implementing native OS features, or packaging web apps for desktop.
finance
Financial analysis expertise for financial modeling (DCF, LBO, M&A), valuation, financial statement analysis, capital allocation, treasury management, and corporate finance decisions. Use when building financial models, analyzing statements, or making investment decisions.
investment-memo-generator
Investment memo creation combining financial analysis, document generation, and structured templates. Use when creating investment memos, pitch decks, deal summaries, or investment committee materials.