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 matematicsolutions/awesome-matematic-skills-pl --skill deliverable-fidelity-plgit clone --depth 1 https://github.com/matematicsolutions/awesome-matematic-skills-plWrote 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/matematicsolutions/awesome-matematic-skills-pl/deliverable-fidelity-pl)<a href="https://agentmods.dev/skills/matematicsolutions/awesome-matematic-skills-pl/deliverable-fidelity-pl"><img src="https://agentmods.dev/badge/skills/matematicsolutions/awesome-matematic-skills-pl/deliverable-fidelity-pl/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/matematicsolutions/awesome-matematic-skills-pl/deliverable-fidelity-pl"><img src="https://agentmods.dev/badge/skills/matematicsolutions/awesome-matematic-skills-pl/deliverable-fidelity-pl.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 | $0.00242 | $0.03280 |
| Opus 5.5 | $0.00097 | $0.01312 |
| Sonnet 5.5 | $0.00048 | $0.00656 |
| Haiku 4.5 | $0.00024 | $0.00328 |
Grade A, and why
deliverable-fidelity-pl 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 21d 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 — 192 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Deliverable Fidelity PL - weryfikator wiernosci dokumentu
Filozofia
Najgrozniejszy blad to nie zly cytat, tylko prawdziwe ustalenie, ktore wypadlo z podsumowania. Analiza znalazla klauzule RED, opinia ma 12 stron, ale w podsumowaniu dla zarzadu tej klauzuli nie ma - bo model "streszczajac" ja pominal. Cytaty sie zgadzaja, teza wytrzymuje atak, a mimo to deliverable klamie przez przemilczenie. Ten skill sprawdza wiernosc: czy to, co wyszlo, oddaje to, co znaleziono.
To trzecia, odrebna os weryfikacji:
citation-grounding-pl- czy cytaty istnieja w zrodle (prawdziwosc).adversarial-legal-review-pl- czy teza wytrzymuje atak (odpornosc).deliverable-fidelity-pl- czy deliverable oddaje analize (wiernosc).
Kiedy odpalac
Gdy finalny dokument streszcza dluzsza analize - opinia z podsumowaniem dla zarzadu, memo DD z tabela ryzyk, raport z sekcja wnioskow. Tam, gdzie skracanie moze zgubic ustalenie. Nie trzeba dla krotkiego pisma bez warstwy "analiza -> streszczenie".
Wejscie
- Ustalenia analizy (findings) - lista z severity i opcjonalnym rozstrzygnieciem:
{ "findings": [ { "id": "F1", "severity": "RED", "tekst": "klauzula limitacji odpowiedzialnosci sprzeczna z art. 473 par. 2 KC", "rozstrzygniecie": "rekomendacja usuniecia" }, { "id": "F2", "severity": "YELLOW", "tekst": "termin platnosci 60 dni - ryzyko zatorow", "rozstrzygniecie": "" } ], "deliverable": "<pelny tekst finalnego dokumentu>" } - Deliverable - finalny tekst do sprawdzenia.
Workflow
- Check mechaniczny (skrypt, za darmo) - uruchom:
Skrypt wyciaga kluczowe terminy z kazdego ustalenia, normalizuje (lowercase, biale znaki, cudzyslowy, myslniki) i stosuje konserwatywny stem (utniecie 2 koncowych znakow przy slowach >=7, by zlapac fleksjenode scripts/fidelity-check.mjs <plik-zadania.json>- "klauzuli" pasuje do "klauzula"), po czym sprawdza, czy wystarczajaco terminow pojawia sie w deliverable.
Per ustalenie:
reprezentowanelubpominiete. Pominiete RED -> blokada (exit 1). Rozstrzygniecia tez sprawdzane.
- "klauzuli" pasuje do "klauzula"), po czym sprawdza, czy wystarczajaco terminow pojawia sie w deliverable.
Per ustalenie:
- Kontrola wyrywkowa LLM (osad) - dla ustalen RED (skrypt podaje liste
najciezsze_do_spotcheck_llm, maks. 3) sprawdz nie tylko obecnosc slow, ale czy sens jest oddany (RED moze byc wspomniany, ale zbagatelizowany - "drobna uwaga" zamiast "klauzula niewazna"). To robi model, nie skrypt - mechaniczny match nie wykryje przeklamania tonu. Gdy brak ustalen RED, ta kontrola odpada (skrypt nie eskaluje YELLOW). - Werdykt - liczony deterministycznie wg funkcji ponizej, nie "na oko".
What ships with it
3 files 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.
- 21d ago Changed · +32 lines 9223e61d0515
- 1mo ago First seen · 160 lines · 242 tokens per session scan A 2991c76aa08c
deliverable-fidelity-pl is a skill published in the GitHub repository matematicsolutions/awesome-matematic-skills-pl (8 stars, last pushed 8d ago), licensed MIT. It adds 242 tokens to every session and 3,280 once invoked, about $0.0010 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 2026-08-31.
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