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 conorbronsdon/agent-skills --skill angel-diligencegit clone --depth 1 https://github.com/conorbronsdon/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/conorbronsdon/agent-skills/angel-diligence)<a href="https://agentmods.dev/skills/conorbronsdon/agent-skills/angel-diligence"><img src="https://agentmods.dev/badge/skills/conorbronsdon/agent-skills/angel-diligence/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/conorbronsdon/agent-skills/angel-diligence"><img src="https://agentmods.dev/badge/skills/conorbronsdon/agent-skills/angel-diligence.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 | $0.00079 | $0.02579 |
| Opus 5 | $0.00039 | $0.01290 |
| Sonnet 5 | $0.00016 | $0.00516 |
| Haiku 4.5 | $0.00008 | $0.00258 |
Grade A, and why
angel-diligence 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.
How it starts
The opening of the file, as written. The whole thing — 106 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/angel-diligence: Pre-Investment Deal Memo
Given a company name (plus optional deck notes, founder names, round details), research the company from public sources and produce a structured deal memo. Every factual claim is cited. Anything unverifiable is labeled. The memo ends in a verdict scaffold, not a recommendation. The human decides.
Invocation: deliberately model-invocable — "diligence [company]" is the trigger. Research is read-only; deck contents never leave the session.
When to Use
- "Diligence [company]" / "research [company] for an angel check"
- "Build a deal memo for [company]"
- Before a founder call, to generate the highest-information questions
- After receiving a deck, to check the claims in it against public evidence
Skip for public companies (use an equity research workflow) and for follow-on rounds where you already hold a position and want a position review.
Evidence Rules (read before researching)
These rules override speed. A short memo with real citations beats a long memo with invented facts.
- Every factual claim needs a fetched source. A claim goes in the memo only if you fetched a page that supports it. Cite the URL inline next to the claim. Model memory is not a source; it is stale by definition for startups.
- "Could not verify" is a valid finding. If a search comes up empty, write "could not verify" next to the claim. Do not fill gaps with plausible guesses. An absence of evidence is itself a signal worth reporting.
- Date everything. Every cited fact gets the date of the source page (or "undated"). Funding databases, team pages, and pricing pages go stale fast. A 14-month-old headcount number presented as current is a hallucination with a citation. Funding data is the worst offender: aggregator databases (Crunchbase mirrors, Tracxn) often miss the latest round or conflate rounds. Prefer the primary announcement, and treat any funding fact older than 6 months as possibly superseded by an unannounced round.
- Separate verified from claimed. Anything sourced only from the company itself (deck, website, founder posts) is "claimed." Anything confirmed by an independent source (customer post, public repo, conference talk by a user) is "verified." Press is verified only when it quotes a customer or third party speaking from their own experience; an article that only quotes the founders or investors is still "claimed." Label each traction item as one or the other.
- No invented numbers. Never state a TAM, ARR, valuation, or growth rate that does not appear in a fetched source. Market sizing must be built bottom-up from cited inputs (number of potential buyers x plausible contract value), with the arithmetic shown.
- Confidentiality: never paste deck contents into web searches. Deck notes the user provides may be under NDA or simply private. Use them to know what to look for, then search in generic terms ("[company] pricing", "[company] customers"). Never put deck numbers, customer names from the deck, or roadmap details into a search query or any other external tool. The company's name and public website are not confidential; use them freely even if you learned them from the deck. Litmus test for any query: could someone who never saw the deck have written it? If not, do not run it.
What ships with it
4 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.
- 12d ago First seen · 106 lines · 79 tokens per session scan A 9197c0717a93
angel-diligence is a skill published in the GitHub repository conorbronsdon/agent-skills (10 stars, last pushed 1mo ago), licensed MIT. It adds 79 tokens to every session and 2,579 once invoked, about $0.0004 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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