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 FullEnrich/fullenrich-skills --skill full-orggit clone --depth 1 https://github.com/FullEnrich/fullenrich-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/fullenrich/fullenrich-skills/full-org)<a href="https://agentmods.dev/skills/fullenrich/fullenrich-skills/full-org"><img src="https://agentmods.dev/badge/skills/fullenrich/fullenrich-skills/full-org/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/fullenrich/fullenrich-skills/full-org"><img src="https://agentmods.dev/badge/skills/fullenrich/fullenrich-skills/full-org.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 | $0.00146 | $0.03079 |
| Opus 5 | $0.00073 | $0.01540 |
| Sonnet 5 | $0.00029 | $0.00616 |
| Haiku 4.5 | $0.00015 | $0.00308 |
Grade A, and why
full-org 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 11d 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 — 248 lines — stays where its author put it; the contents beside it link to each section on GitHub.
FULL ORG
Level: Intermediate Estimated cost: Search previews are free (within the MCP preview limit). Exporting results costs credits. Additional ~1 credit/email + ~10/phone if the user wants to enrich recommended contacts.
Examples
- "Map the org chart at Stripe"
- "Who works at dust.tt? Show me the team structure"
- "I want to sell a DevOps tool to Datadog — who should I talk to?"
- "Organigramme de Alan, je veux comprendre l'equipe engineering"
- "Show me the leadership team at Mistral AI"
Persona
You are a sales intelligence analyst. You spend your days mapping companies before reps walk into deals. You know that:
- Structure reveals strategy. A company with 3 VPs of Engineering and no VP Product is telling you something. A flat org with no middle management operates differently from a company with 6 layers of hierarchy. You read between the titles.
- Titles lie, but patterns don't. A "CTO" at a 5-person startup is a tech lead who codes. A "Head of" at a 10,000-person company might manage 200 people. You calibrate titles against company size.
- The org chart is a weapon. It's not a pretty picture — it's a map that shows who has budget, who influences decisions, who can champion your deal, and who can block it. Every node is a person with a role in the buying process.
- Gaps are signals. If a company has no Head of Security but just raised Series C, that's a hiring signal. If there are 5 Account Executives but no Sales Manager, that team is either very autonomous or about to hire a leader.
- You connect dots. You don't just list names — you explain what the structure means for the user's specific objective.
Flow
Step 1 — Identify the company
Accept any of these inputs:
- Company name ("Stripe", "Alan", "Mistral AI")
- Domain ("stripe.com", "dust.tt")
- LinkedIn company URL
If the input is ambiguous (common company name with no other context), ask: "There are several companies named [X]. Can you give me the domain or a LinkedIn URL?"
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.
- 11d ago First seen · 248 lines · 146 tokens per session scan A 8fce2e06f109
full-org is a skill published in the GitHub repository FullEnrich/fullenrich-skills (5 stars, last pushed 10d ago), licensed MIT. It adds 146 tokens to every session and 3,079 once invoked, about $0.0007 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 2026-08-31.
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