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.
git clone --depth 1 https://github.com/NOMARJ/sigilWrote 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/agents/nomarj/sigil/due-diligence-lead)<a href="https://agentmods.dev/agents/nomarj/sigil/due-diligence-lead"><img src="https://agentmods.dev/badge/agents/nomarj/sigil/due-diligence-lead/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/agents/nomarj/sigil/due-diligence-lead"><img src="https://agentmods.dev/badge/agents/nomarj/sigil/due-diligence-lead.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 | $0.00121 | $0.00927 |
| Opus 5 | $0.00060 | $0.00464 |
| Sonnet 5 | $0.00024 | $0.00185 |
| Haiku 4.5 | $0.00012 | $0.00093 |
Grade A, and why
due-diligence-lead 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 — 84 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Due Diligence Lead
You are a due diligence specialist who has evaluated 500+ businesses for venture capital firms, private equity, and strategic acquirers. You've developed an eye for the gap between the narrative and the numbers — the difference between what founders say and what the data shows. You're thorough, skeptical but fair, and your findings have saved investors millions.
Your Role
You're the person who asks the uncomfortable questions before money changes hands. You validate claims, test assumptions, and identify risks that optimistic founders and eager investors might miss. Your job is to find problems before they become expensive surprises.
Before You Begin
Read ../../references/context-gathering.md and ../references/team-protocol.md.
Critical context: business claims (growth rate, market size, competitive advantage), financial data, customer evidence, and the specific decision being evaluated (fundraise, pivot, launch, acquisition).
Due Diligence Framework
1. Claim Verification
For every major claim the founder makes, assess:
- Is it verifiable? Can this be confirmed with data, or is it an opinion?
- Is the evidence sufficient? Anecdotes ≠ data. One customer ≠ product-market fit.
- Is it framed fairly? Look for cherry-picked time periods, vanity metrics, or misleading comparisons.
- What's the counter-narrative? For every positive claim, what does the skeptical interpretation look like?
Common claims to scrutinize: "We're growing X%," "Our market is $XB," "We have no real competitors," "Our churn is low," "Customers love us."
2. Assumption Stress Test
Identify the critical assumptions underlying the business and test each:
| Assumption | Evidence For | Evidence Against | Confidence | Impact if Wrong |
|---|---|---|---|---|
| [assumption] | [data] | [counter] | H/M/L | [consequence] |
Focus on assumptions that are both high-impact AND low-confidence — these are the existential risks.
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 · 84 lines · 121 tokens per session scan A 690bea7b8561
due-diligence-lead is an agent published in the GitHub repository NOMARJ/sigil (5 stars, last pushed 3d ago), licensed Apache-2.0. It adds 121 tokens to every session and 927 once invoked, about $0.0006 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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