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 zgbrenner/agentcounsel --skill data-room-index-reviewgit clone --depth 1 https://github.com/zgbrenner/agentcounselWrote 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/zgbrenner/agentcounsel/data-room-index-review)<a href="https://agentmods.dev/skills/zgbrenner/agentcounsel/data-room-index-review"><img src="https://agentmods.dev/badge/skills/zgbrenner/agentcounsel/data-room-index-review/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/zgbrenner/agentcounsel/data-room-index-review"><img src="https://agentmods.dev/badge/skills/zgbrenner/agentcounsel/data-room-index-review.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 | $0.00034 | $0.02578 |
| Opus 5 | $0.00017 | $0.01289 |
| Sonnet 5 | $0.00007 | $0.00516 |
| Haiku 4.5 | $0.00003 | $0.00258 |
Grade A, and why
Data Room Index Review 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.
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 — 215 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Data Room Index Review
Purpose
Review a merger or acquisition data room index — or an uploaded file list — and identify, from a stated side of the deal, which diligence categories the index shows as covered, which appear partial or absent, and what follow-up requests the index suggests. The review works from the index as metadata: folder and file names, counts, and dates. It does not open or read the underlying documents.
This skill produces draft work product for attorney review only. It is not legal advice and is not a conclusion that diligence is complete or adequate. What a data room index shows is a list of files; whether the diligence behind those files is sufficient is a judgment for the deal team and counsel.
Use When
- A user asks to "review our data room index," "check this file list for gaps," "what's missing from the data room," or "what should we still ask the other side for."
- A deal team needs a structured read of a data room index before diligence begins, mid-process, or as a coverage check before signing.
- A seller-side team needs to check its own index for completeness, duplicates, or naming problems before opening the room.
Required Inputs
- The data room index or file list — uploaded or pasted. Do not review from a description, a summary, or a recollection of what the room contains.
- The deal type — for example a stock purchase, asset purchase, merger, membership-interest purchase, or carve-out.
- The side the review is for — buyer-side or seller-side.
- The expected diligence scope — the diligence categories the deal team expects to cover, and any known focus areas (for example, IP, employment, or environmental).
- Jurisdiction and governing law — as relevant to scope, or flagged as unknown.
- Any related material — a diligence request list, a prior index version, or a process letter — if it exists.
If the index, the deal type, or the side is not provided, stop and request it. Do not review an index you have not been given, and do not assume the side.
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.
- 9d ago First seen · 215 lines · 34 tokens per session scan A 5016c0694e3d
Data Room Index Review is a skill published in the GitHub repository zgbrenner/agentcounsel (19 stars, last pushed 1mo ago), licensed MIT. It adds 34 tokens to every session and 2,578 once invoked, about $0.0002 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 2026-09-03.
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