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legal-diagram

legal-diagram is a skill for Claude Code from nanparth/ai-skill-hub. It costs 113 tokens per session (2,282 once invoked), scanned A, original, MIT.

A tool for turning legal or legal-adjacent material into Mermaid diagrams, such as timelines, party maps, obligation maps, and compliance workflows. Mermaid is a text-based format for generating diagrams.

In plain words
What is it for?
Use it to diagram contracts, deals, legal matters, corporate structures, money flows, obligations, timelines, and compliance processes.
Why use it?
It helps organise complex legal information visually while preserving the relationships and sequence in the source material. It can optionally produce a downloadable HTML figure.

Skill for Claude Code

Written for Claude Code: argument-hint in frontmatter.

not rated 23repo 20d ago A scan 113 tokens original MIT

Good fit Use it to diagram contracts, deals, legal matters, corporate structures, money flows, obligations, timelines, and compliance processes.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/nanparth/ai-skill-hub/legal-diagram
View source ↗ nanparth/ai-skill-hub
Install

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.

Any agent
npx skills add nanparth/ai-skill-hub --skill legal-diagram
Clone the repo
git clone --depth 1 https://github.com/nanparth/ai-skill-hub

Made for: Claude Code.

Wrote 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.

agentmods badge for legal-diagram

README.md
[![agentmods](https://agentmods.dev/badge/skills/nanparth/ai-skill-hub/legal-diagram/github.svg)](https://agentmods.dev/skills/nanparth/ai-skill-hub/legal-diagram)
Your own site
<a href="https://agentmods.dev/skills/nanparth/ai-skill-hub/legal-diagram"><img src="https://agentmods.dev/badge/skills/nanparth/ai-skill-hub/legal-diagram/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.

agentmods 80×15 button for legal-diagram

Your own site · 80×15
<a href="https://agentmods.dev/skills/nanparth/ai-skill-hub/legal-diagram"><img src="https://agentmods.dev/badge/skills/nanparth/ai-skill-hub/legal-diagram.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 113 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,282 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00113 $0.02282
Opus 5 $0.00056 $0.01141
Sonnet 5 $0.00023 $0.00456
Haiku 4.5 $0.00011 $0.00228

Measured 12d ago against content hash cde698ebf3b7, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

legal-diagram 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.

The scan reads SKILL.md. This mod also ships 53 executable files (scripts/check_setup.py, scripts/diagram_selector.py, scripts/eval_pass2.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

legal-diagram/SKILL.md · 112 lines

How it starts

The opening of the file, as written. The whole thing — 112 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Standalone skill: turn legal material into a context-appropriate Mermaid diagram, with an optional downloadable HTML figure. A structure-preserving Python engine extracts a typed ground truth; directive-driven LLM enrichment fills the gaps; a selector picks the diagram type; the diagram is generated natively.

Routing gate

Every real diagram request runs in this fixed order: first-run check, ingest, build-mode gate, generate, report gate. Non-diagram intents short-circuit at Step 0.

Three human gates = mandatory hard stops: GATE 0 (tutorial offer), GATE A (build mode), GATE B (HTML report). Gate discipline, no exceptions:

  • Present each as structured choice (the question tool). No such tool → numbered plain-text list. Either way, STOP, wait for reply.
  • Never skip a gate. Never infer its answer from wording. Never generate past an unanswered gate. Detailed, specific, or named-diagram request = still a request, not a gate answer.
  • Only a literal typed flag may pre-answer: --direct/--guided (GATE A), --html (GATE B), --tutorial (tutorial). Nothing else counts.

Step 0 — Intent and first-run

Check explicit short-circuits first:

  1. Tutorial signals: "tutorial", "show me how", "first time", "demo", "walk me through", --tutorial. → Load workflows/tutorial.md. Stop here.
  2. Setup signals: "check setup", "install deps", "is setup ready". → Load shared/setup-check.md, run check_setup.py, report. Stop here.

Otherwise this is a real diagram request (a file, pasted text, or a matter description). Detect first-run:

Run python scripts/first_run.py. Parse {state}: returning, first_run, or unknown. Script absent, non-zero exit, or no JSON → treat as unknown.

  • returning (confirmed) → no offer; user ran skill before. Continue to Step 1.
  • first_run, unknown, or anything not a confirmed returning → GATE 0 (hard stop): "First time here. Want a quick tutorial, or go straight to your diagram?" Options: Start tutorial (recommended, list first) / Skip, straight to my diagram. Present as structured choice, or numbered plain-text list if host has no choice tool, then STOP, wait for reply. After answer, run python scripts/first_run.py --mark to record offer (best-effort; on unknown state with no writable disk, mark may not persist, fine). Then: tutorial → load workflows/tutorial.md, stop; skip → continue to Step 1.

Read the full file on GitHub · 112 lines

Files

What ships with it

60 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.

Changes

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.

  1. 12d ago First seen · 112 lines · 113 tokens per session scan A cde698ebf3b7

Subscribe to this mod's changes

legal-diagram is a skill published in the GitHub repository nanparth/ai-skill-hub (23 stars, last pushed 20d ago), licensed MIT. It adds 113 tokens to every session and 2,282 once invoked, about $0.0006 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 2026-08-30.

Creative and mediaLegal and compliance
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