diligence-deck

diligence-deck is a skill for Claude Code, Codex from Rockielab/rockie-codex. It costs 65 tokens per session (6,921 once invoked), scanned A, a copy of diligence-deck, Apache-2.0.

A workflow for reviewing a company acquisition using information from a private data room, the collection of documents shared for the review, plus deal inputs and supporting web research.

In plain words
What is it for?
Use it to ingest and reconcile data-room files, research an acquisition, produce structured due-diligence findings, and prepare or review an investment-committee deck.
Why use it?
It turns source material into findings that can be checked against named documents or web citations, while including review by a skeptical critic.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions subagents.

Good fit Use it to ingest and reconcile data-room files, research an acquisition, produce structured due-diligence findings, and prepare or review an investment-committee deck.

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Install with agentmods
npx agentmods add skills/rockielab/rockie-codex/diligence-deck
Install

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.

Any agent
npx skills add Rockielab/rockie-codex --skill diligence-deck
Clone the repo
git clone --depth 1 https://github.com/Rockielab/rockie-codex

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for diligence-deck

README.md
[![agentmods](https://agentmods.dev/badge/skills/rockielab/rockie-codex/diligence-deck/github.svg)](https://agentmods.dev/skills/rockielab/rockie-codex/diligence-deck)
Your own site
<a href="https://agentmods.dev/skills/rockielab/rockie-codex/diligence-deck"><img src="https://agentmods.dev/badge/skills/rockielab/rockie-codex/diligence-deck/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.

agentmods 80×15 button for diligence-deck

Your own site · 80×15
<a href="https://agentmods.dev/skills/rockielab/rockie-codex/diligence-deck"><img src="https://agentmods.dev/badge/skills/rockielab/rockie-codex/diligence-deck.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 65 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 6,921 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 100% copy Near-identical to another mod in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00065 $0.06921
Opus 5 $0.00032 $0.03460
Sonnet 5 $0.00013 $0.01384
Haiku 4.5 $0.00006 $0.00692

Measured 9d ago against content hash f0f96e2eece1, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

diligence-deck 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 9d ago.

The scan reads SKILL.md. This mod also ships 6 executable files (scripts/battleground.py, scripts/critic_loop.py, scripts/fetch_dataroom.sh, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

Origin

This is a copy

100% identical to diligence-deck — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

project-extension/agents/skills/diligence-deck/SKILL.md · 502 lines

How it starts

The opening of the file, as written. The whole thing — 502 lines — stays where its author put it; the contents beside it link to each section on GitHub.

diligence-deck — acquisition due-diligence findings for Atlas

Explicit goal

You are a senior consultant at a top-tier firm (EY-Parthenon / L.E.K. / Bain DD practice) producing acquisition due-diligence findings for an investment committee (IC). Your output must survive review by a skeptical senior partner who flags vague claims, unsupported numbers, paraphrased citations, hedges, and asymmetric depth as slop and sends it back. Every finding maps to a verbatim quote from a named data-room document or a web citation. Nothing is invented. Nothing is paraphrased into a number.

This skill covers A1 + A2 + A3 + A5: (A5 fetch) -> intake -> ingest -> reconcile -> research -> structured findings -> deck -> adversarial critic loop -> (A5 emit). A1 produces findings.json + findings.md; A2 ("Deck rendering") renders that typed contract into a partner-grade slide deck; A3 ("Adversarial critic loop") runs a fresh senior-partner critic until the run passes twice; A5 ("Connectors") wires the running Rockie lab's uploaded sources in as the data room and ships the deck back out as a downloadable artifact. One later slice extends it — do not attempt its work here:

  • A1b — swap the built-in research step for a bake-off-selected deep-research engine.

Pipeline

[1] INTAKE     — deal inputs (company, sector, ask price, thesis, prior
                 knowledge). Save to deal_inputs.md.
[2] INGEST     — scripts/ingest_dataroom.sh <dataroom> -> manifest.json
[3.5] RECONCILE — scripts/reconcile.py <manifest> -> reconcile.json.
                 Cross-document contradiction scan + missing-but-expected
                 fields. Runs BEFORE synthesis. Its deltas are first-class
                 inputs the findings MUST address.
[3] RESEARCH   — TWO separated sub-steps, never collapsed:
                 [3a] RETRIEVE: read manifest docs + web search; collect
                      verbatim evidence (quote + source) into an evidence
                      pool. The retriever does NOT write findings.
                 [3b] SYNTHESIZE: write each section ONLY from the evidence
                      pool. The synthesizer may not introduce a fact or a
                      number that is not already in the pool with a quote.
[4] FINDINGS   — emit findings.json (typed contract for A2) + findings.md.

Read the full file on GitHub · 502 lines

Changes

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.

  1. 9d ago First seen · 502 lines · 65 tokens per session scan A f0f96e2eece1

Subscribe to this mod's changes

diligence-deck is a skill published in the GitHub repository Rockielab/rockie-codex (20 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 65 tokens to every session and 6,921 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to diligence-deck, differing in 0 lines, and is treated as a copy.

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