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 moonlight-lupin/agent-skills --skill entity-researchgit clone --depth 1 https://github.com/moonlight-lupin/agent-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/moonlight-lupin/agent-skills/entity-research)<a href="https://agentmods.dev/skills/moonlight-lupin/agent-skills/entity-research"><img src="https://agentmods.dev/badge/skills/moonlight-lupin/agent-skills/entity-research/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/moonlight-lupin/agent-skills/entity-research"><img src="https://agentmods.dev/badge/skills/moonlight-lupin/agent-skills/entity-research.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00191 | $0.02615 |
| Opus 5.5 | $0.00076 | $0.01046 |
| Sonnet 5.5 | $0.00038 | $0.00523 |
| Haiku 4.5 | $0.00019 | $0.00262 |
Grade A, and why
entity-research 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 20d 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 — 123 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Entity Research
Deep background research on a company or a person → a cited dossier for a human to read and act on. General-purpose research — vetting a vendor, a counterparty before a contract, a prospective hire, a partner, or verifying a media claim.
Research & compilation — NOT a determination. This skill does not screen, clear, rate, or block anyone. A sanctions-list / PEP / watchlist signal is a SIGNAL to escalate to a qualified compliance / AML function, not a finding; negative press is an allegation with a source and date, not a proven fact. Everything is cited; nothing is auto-acted on.
Scope and routing
Use this skill for general background research and fast public signals. Do not use it as a substitute for professional CDD/AML screening, sanctions clearance, PEP screening, or a compliance decision, and do not build an intrusive profile of a private individual.
When to use it
- Vet a vendor / supplier / counterparty before engaging or signing a contract.
- Background on a prospective hire, a partner, or a co-investor's principal.
- Check for negative / adverse media or litigation on a name.
- A quick public sanctions-list signal check (to escalate, not to clear).
- A quick PEP indication check from public research (to escalate, not to clear).
- "Who actually owns / runs X?" — ownership & key-management background.
The research lenses
- Identity & background — confirm you have the right entity (registration no., jurisdiction, incorporation date, website, aliases / former names; for a person: role, employer, location, DOB if public). Disambiguate same-name entities early.
- Ownership & key management — shareholders / UBO signals, directors, senior managers; group/parent structure. Use the
people-enrichmentskill / PDL for people & firmographics where appropriate. - Adverse / negative media — allegations, investigations, scandals, insolvency, fraud, environmental/labour issues — each with source, date, and allegation-vs-outcome.
- Sanctions / PEP / watchlist signals —
screen_lists(name)checks public sanctions lists only (OFAC SDN + Consolidated, UK OFSI, UN). PEP indications are manual/open-web research signals, such as public office, senior state-owned enterprise role, close-associate indications, or official biographies. Neither is a clearance. - Litigation & regulatory — material lawsuits, regulator actions, fines, debarments.
- Summary & flags — a short read with escalation flags for a compliance reviewer.
What ships with it
6 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.
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.
- 20d ago Changed · -12 lines · +1 tokens per session 38c7f6277fd5
- 1mo ago First seen · 135 lines · 190 tokens per session scan A aa26e3ee7845
entity-research is a skill published in the GitHub repository moonlight-lupin/agent-skills (112 stars, last pushed 4d ago), licensed MIT. It adds 191 tokens to every session and 2,615 once invoked, about $0.0008 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.
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