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/ThomasMoreAI/legal-skills-opennpx agentmods add skills/thomasmoreai/legal-skills-open/recht-report-pdf-momarcode1Wrote 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/thomasmoreai/legal-skills-open/recht-report-pdf-momarcode1)<a href="https://agentmods.dev/skills/thomasmoreai/legal-skills-open/recht-report-pdf-momarcode1"><img src="https://agentmods.dev/badge/skills/thomasmoreai/legal-skills-open/recht-report-pdf-momarcode1/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/thomasmoreai/legal-skills-open/recht-report-pdf-momarcode1"><img src="https://agentmods.dev/badge/skills/thomasmoreai/legal-skills-open/recht-report-pdf-momarcode1.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 | $0.00031 | $0.03834 |
| Opus 5.5 | $0.00012 | $0.01534 |
| Sonnet 5.5 | $0.00006 | $0.00767 |
| Haiku 4.5 | $0.00003 | $0.00383 |
Grade A, and why
recht-report-pdf-momarcode1 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.
How it starts
The opening of the file, as written. The whole thing — 376 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/recht report-pdf -- PDF-Bericht generieren
Generates a professional PDF legal report from all previous /recht analysis results in the current conversation. Combines contract review scores, risk analysis, claim identification, evidence evaluation, cost calculations, litigation strategy, and compliance findings into a single branded PDF document.
Step 1: Check Prerequisites
Before anything else, verify that the reportlab Python package is available.
Run via Bash tool:
python3 -c "import reportlab; print(reportlab.Version)"
- If this succeeds: proceed to Step 2 (RIS Verification) and then Step 3.
- If this fails with
ModuleNotFoundError: STOP. Tell the user:
reportlab ist nicht installiert. Bitte fuehren Sie folgenden Befehl aus:
pip3 install reportlabDanach koennen Sie
/recht report-pdferneut ausfuehren.
Do NOT proceed without reportlab. Do NOT attempt to install it automatically.
Also verify the PDF generation script exists. Check for scripts/generate_legal_pdf.py relative to the project root (the directory containing CLAUDE.md for this project). If it does not exist, tell the user the script is missing and cannot proceed.
Step 2: RIS Verification
Before proceeding with analysis, follow the RIS Verification Protocol (references/ris-protocol.md):
- Check RIS MCP availability
- For every § you cite in this analysis, verify current wording via RIS
- For case law references, retrieve via RIS Justiz
- Record verification status for the Quellenstatus block
- If RIS is unavailable, follow the fallback ladder and flag all affected citations
Step 3: Collect Data from Current Session
Review the ENTIRE current conversation history and gather ALL results from previous /recht commands. You must look for outputs from each of the following sub-commands. For each one found, extract the structured data described below.
3a: From /recht review (Vertragspruefung)
Look for:
- Vertragssicherheits-Score: the numeric score (0-100) and letter grade (A-F)
- Risk dashboard counts: number of critical (rot), important (gelb), and standard (gruen) findings
- Clause-by-clause analysis: each analyzed clause with its risk level, identified problem, applicable law reference (paragraph citations), and recommendation
- Formulierungsvorschlaege: any suggested replacement text for problematic clauses
- Document metadata: document name, document type (Kaufvertrag, Mietvertrag, Arbeitsvertrag, AGB, etc.), parties involved
What ships with it
2 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.
- 12d ago Changed · +3 lines 564554b6222f
- 14d ago First seen · 373 lines · 31 tokens per session scan A be0afaaabfff
recht-report-pdf-momarcode1 is a skill published in the GitHub repository ThomasMoreAI/legal-skills-open (88 stars, last pushed 4d ago), licensed Apache-2.0. It adds 31 tokens to every session and 3,834 once invoked, about $0.0001 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 2026-10-02.
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