p0-regulatory

p0-regulatory is a command for coding agents from jonase47/ccpr. It costs 0 tokens per session (1,153 once invoked), scanned A, original, MIT.

A command that identifies relevant laws, GDPR duties, and legal reasons an idea might have to stop before detailed development begins. GDPR is the European Union's data-protection law.

In plain words
What is it for?
Use it for an initial review of areas such as health data, financial services, or children's applications, based on the project's problem and market context.
Why use it?
It helps reveal legal showstoppers early, when changing the idea is still easier and cheaper.

Command

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.

agentmods
npx agentmods add commands/jonase47/ccpr/p0-regulatory
Clone the repo
git clone --depth 1 https://github.com/jonase47/ccpr

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 p0-regulatory

README.md
[![agentmods](https://agentmods.dev/badge/commands/jonase47/ccpr/p0-regulatory.svg)](https://agentmods.dev/commands/jonase47/ccpr/p0-regulatory)
Your own site
<a href="https://agentmods.dev/commands/jonase47/ccpr/p0-regulatory"><img src="https://agentmods.dev/badge/commands/jonase47/ccpr/p0-regulatory.svg" alt="Measured on agentmods" height="20"></a>
Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,153 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00000 $0.01153
Opus 5 $0.00000 $0.00576
Sonnet 5 $0.00000 $0.00231
Haiku 4.5 $0.00000 $0.00115

Measured today against content hash 5c5ecdaa3095, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

p0-regulatory 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 today.

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.

commands/p0-regulatory.md · 85 lines

How it starts

The opening of the file, as written. The whole thing — 85 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Identifies regulatory requirements, DSGVO (GDPR) obligations, and legal knock-out criteria early on, before significant time is invested in the idea. A regulatory showstopper should be recognised as early as possible.

Argument: $ARGUMENTS = [Area, e.g. "health data", "financial services", "children's app"]

If provided: Use as the focus for the regulatory check. If not provided: Read DISCOVERY.md to understand the context (Target Audience, data, industry). If context is missing, ask for the relevant area.

Execution

1. Read Context

Read docs/discovery/DISCOVERY.md (phase index), docs/discovery/PROBLEM.md (problem statement, Target Audience), and docs/discovery/MARKET.md (market context) to understand which regulatory areas are relevant.

2. Delegate to security-master Agent (Lead)

Delegate the regulatory analysis to the security-master agent:

Conduct a first regulatory assessment for the following area: $ARGUMENTS Context from PROBLEM.md and MARKET.md: [Insert problem statement, Target Audience, industry]

Check and evaluate:

  1. DSGVO Relevance: What personal data is processed? Which articles apply (Art. 6, Art. 9, Art. 13/14)?
  2. Sector-Specific Regulation: Are there specific laws or regulations (e.g. MDR for medical devices, DiGA, FINMA, GwG)?
  3. Licences and Certifications: Are permits required?
  4. Knock-Out Criteria: What could legally stop or massively delay the project?
  5. Assessment: 🟢 No significant hurdles / 🟡 Hurdles, but surmountable / 🔴 Critical knock-out criterion

Be concrete and practical. Cite relevant laws/regulations.

3. Delegate to konzeptor Agent (Support)

Delegate the classification in the project context to the konzeptor agent:

Evaluate the regulatory findings of the security-master: Are the identified hurdles acceptable? What impact do they have on the Concept (scope, timeline, costs)?

4. Write Detail File

Write the result to docs/discovery/REGULATORY.md (overwrite if it exists). Start with this YAML frontmatter:

Read the full file on GitHub · 85 lines

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. today Changed · +3 lines 5c5ecdaa3095
  2. 3d ago First seen · 82 lines · 0 tokens per session scan A 1b09beec7059

Subscribe to this mod's changes

p0-regulatory is a command published in the GitHub repository jonase47/ccpr (1 stars, last pushed today), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,153 tokens. 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.