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/dithiothreitol/jdg-ksiegowynpx agentmods add skills/dithiothreitol/jdg-ksiegowy/doctorWrote 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/dithiothreitol/jdg-ksiegowy/doctor)<a href="https://agentmods.dev/skills/dithiothreitol/jdg-ksiegowy/doctor"><img src="https://agentmods.dev/badge/skills/dithiothreitol/jdg-ksiegowy/doctor/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/dithiothreitol/jdg-ksiegowy/doctor"><img src="https://agentmods.dev/badge/skills/dithiothreitol/jdg-ksiegowy/doctor.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 | $0.00091 | $0.00627 |
| Opus 5 | $0.00046 | $0.00313 |
| Sonnet 5 | $0.00018 | $0.00125 |
| Haiku 4.5 | $0.00009 | $0.00063 |
Grade A, and why
doctor 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 11d 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
Doctor — sprawdzanie konfiguracji
Waliduje .env i obecność plików (certyfikaty, klucze) przed wysyłką do KSeF/MF. Nie dotyka sieci.
Wywołanie
# Raport tekstowy
python3 skills/doctor/scripts/check.py
# Format JSON
python3 skills/doctor/scripts/check.py --format json
# Exit code != 0 gdy są błędy (do CI)
python3 skills/doctor/scripts/check.py --fail-on-error
Co sprawdza
[SELLER] — dane sprzedawcy z .env:
SELLER_NIP(z walidacją sumy kontrolnej)SELLER_NAME,SELLER_ADDRESS,SELLER_BANK_ACCOUNT/NAMESELLER_EMAIL,SELLER_FIRST_NAME/LAST_NAME,SELLER_BIRTH_DATE,SELLER_TAX_OFFICE_CODE(dla JPK)
[KSEF]:
KSEF_ENV(test/demo/prod), pochodny URL APIKSEF_NIP+KSEF_TOKEN
[MF] (bramka JPK):
MF_ENV(test/prod), pochodny URLMF_PESEL(z walidacją),MF_CERT_PATH/MF_CERT_URL
[SMTP] — wysyłka email (opcjonalne):
SMTP_HOST,SMTP_USERNAME,SMTP_PASSWORD
[OCR] — provider i klucze:
OCR_PROVIDER(auto/ollama/claude),ANTHROPIC_API_KEYjeśli claude
Poziomy
- OK — obszar gotowy
- WARN — brak nieblokujący (np. SMTP) — część funkcjonalności niedostępna
- ERROR — krytyczny — wysyłka zadziała dopiero po naprawie
Flow po doctor
Jeśli wszystko OK → możesz ruszać z wysyłkami:
# Dry-run na sandboxie KSeF
python3 skills/ksef/scripts/submit.py --dry-run --invoice-file faktury/A1.xml
# Dry-run JPK (sandbox MF)
python3 skills/jpk-submit/scripts/submit.py --dry-run data/jpk/JPK_V7M_04_2026.xml
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.
- 11d ago First seen · 60 lines · 91 tokens per session scan A e7fd0485fb1a
doctor is a skill published in the GitHub repository dithiothreitol/jdg-ksiegowy (5 stars, last pushed 1mo ago), licensed MIT. It adds 91 tokens to every session and 627 once invoked, about $0.0005 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.
Other skills, from other repositories
tax-calculator
Calculate tax implications of trades and generate tax reports.
jangbu-import
A data-import workflow for turning bank files, card records, spreadsheets, receipts, tax invoices, and statement PDFs into a standard set of 13 transaction fields. OCR, or optical character recognition, is used to read information from document images and PDFs.
jangbu-connect
A setup guide for connecting Korean tax, bank, card, and social-insurance data through CODEF, an external API service. It explains how users obtain their own CODEF credentials and store them locally.
jangbu-tax
A financial-reporting tool that summarizes categorized transactions into a profit-and-loss statement and a simplified balance sheet. A profit-and-loss statement covers income and expenses over a period; a balance sheet shows assets, liabilities, and equity at a date.
accountant-expert
Expert-level accounting, tax, financial reporting, and accounting systems. Use when the user mentions accounting, tax, financial reporting, GAAP, or IFRS, or when the task involves Accounting Principles, Financial Statements, Tax & Compliance, or Accounting Systems.
jaz-recipes
Use this skill when modeling complex multi-step accounting transactions — anything that spans multiple periods, involves changing amounts, or requires linked entries. Covers 16 IFRS-compliant recipes (prepaid amortization, deferred revenue, loans, IFRS 16 leases, hire purchase, fixed deposits, asset disposal, FX…