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 mishahanin/heading-os --skill data-roomgit clone --depth 1 https://github.com/mishahanin/heading-osWrote 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/mishahanin/heading-os/data-room)<a href="https://agentmods.dev/skills/mishahanin/heading-os/data-room"><img src="https://agentmods.dev/badge/skills/mishahanin/heading-os/data-room/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/mishahanin/heading-os/data-room"><img src="https://agentmods.dev/badge/skills/mishahanin/heading-os/data-room.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 | $0.00067 | $0.01696 |
| Opus 5.5 | $0.00027 | $0.00678 |
| Sonnet 5.5 | $0.00013 | $0.00339 |
| Haiku 4.5 | $0.00007 | $0.00170 |
Grade A, and why
data-room 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 1mo 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 — 168 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Data Room - Investor Due Diligence & Fundraising Preparation
Prepare structured documents for investor data rooms, respond to due diligence questions, and build fundraising materials.
Variables
type: overview | financial-summary | market-analysis | team-overview | technology-brief | competitive-landscape | dd-response | full-room
question: [For dd-response: paste the specific due diligence question or questionnaire]
investor_type: strategic | vc | sovereign | pe — default: strategic
stage: pre-meeting | diligence | term-sheet
Instructions
Before preparing, read ALL relevant files:
canon/reference/context/business-info.md— Company structure, product, partners, teamledger/measurement/context/current-data.md— Metrics, milestones, timelines, market datacanon/position/context/strategy.md— Strategic arc, go-to-market, valuation pathstatus/matter/context/pipeline.md— Active deals and investor conversationscanon/reference/reference/billion-growth-playbook.md— Valuation mechanics, growth model, target-valuation pathcanon/reference/reference/dpi-market-intelligence.md— Market size, competitive landscapecanon/reference/reference/geopolitical-landscape.md— Regional dynamics supporting the thesiscanon/reference/datastore/INDEX.md— If the document contains specific facts or numbers, validate against source documents
Document Types
Company Overview (2-3 pages)
Executive summary for the data room front page:
- Company mission and founding story (December 2024, incumbent vacuum, strategic investor)
- Product: ODUN.ONE platform - what it does, why it matters
- Market opportunity: $25B market, 22% CAGR, 56-country vacuum
- Traction: [region] deployment (live), [region] (in progress), partner network activated
- Team: [N]+ Tribe members, Research Lab, patent portfolio
- Ask and use of funds (if applicable)
Financial Summary
- Current burn rate and runway context
- Revenue model: perpetual license ([$ per Gb/s]) + annual support ([%]) + lifecycle extension
- Bundle pricing: Essential (1.0x) / Professional (1.40x) / Enterprise (1.65x)
- Unit economics: single deployment value ($2.5M+ for 180 Gb/s country)
- Revenue projections framework based on pipeline and geographic phasing
- Path to profitability thesis
What ships with it
1 file 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.
- 1mo ago Changed 67cd15ddf4cb
- 1mo ago Changed · +1 lines bfc5d905b241
- 1mo ago Changed · +1 lines 7586d1d69ed0
- 1mo ago First seen · 166 lines · 67 tokens per session scan A 25f67720748d
data-room is a skill published in the GitHub repository mishahanin/heading-os (11 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 67 tokens to every session and 1,696 once invoked, about $0.0003 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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