Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/cynco-labs/ai-accounting-skillsnpx agentmods add skills/cynco-labs/ai-accounting-skills/generate-workbookWrote 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/cynco-labs/ai-accounting-skills/generate-workbook)<a href="https://agentmods.dev/skills/cynco-labs/ai-accounting-skills/generate-workbook"><img src="https://agentmods.dev/badge/skills/cynco-labs/ai-accounting-skills/generate-workbook/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/cynco-labs/ai-accounting-skills/generate-workbook"><img src="https://agentmods.dev/badge/skills/cynco-labs/ai-accounting-skills/generate-workbook.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 | $0.00022 | $0.00351 |
| Opus 5 | $0.00011 | $0.00176 |
| Sonnet 5 | $0.00004 | $0.00070 |
| Haiku 4.5 | $0.00002 | $0.00035 |
Grade A, and why
generate-workbook 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.
What it actually says
/generate-workbook
Purpose
Single-pass Excel working papers for human review and client packs.
Uses openpyxl (Python). Does not require Microsoft Excel to generate. Formulas are written as strings — values appear when the file is opened/recalculated.
See shared/excel_deliverables.md.
Ledger SoR after finalisation: Beancount (export-beancount), not this xlsx.
Script
pip install openpyxl # or: pip install -r requirements.txt
python3 scripts/generate_workbook.py <input.json> <output.xlsx>
Expected sheets (minimum)
- Company Info
- Chart of Accounts
- Bank Transactions
- Payroll Summary
- Fixed Asset Register
- Journal Entries
- General Ledger
- Trial Balance
- Income Statement
- Balance Sheet
- Tax Computation
- Queries & Notes
Process
- Assemble classified data + ATB + YE JEs into the script’s input JSON format.
- Run the generator.
- Verify file opens; spot-check TB/BS.
- Machine truth remains in
workpapers/*.json— do not invent numbers in Excel only.
Optional: scripts/generate_pdf_report.py (reads xlsx via openpyxl, needs reportlab).
Completion
Done when: workbook opens without corruption and key sheets tie to JSON workpapers/TB.
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 · 56 lines · 22 tokens per session scan A 146ca1e3ab81
generate-workbook is a skill published in the GitHub repository cynco-labs/ai-accounting-skills (3 stars, last pushed 2mo ago), licensed MIT. It adds 22 tokens to every session and 351 once invoked, about $0.0001 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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