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.
git clone --depth 1 https://github.com/avelikiy/great_ctoWrote 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/agents/avelikiy/great_cto/gdpr-reviewer)<a href="https://agentmods.dev/agents/avelikiy/great_cto/gdpr-reviewer"><img src="https://agentmods.dev/badge/agents/avelikiy/great_cto/gdpr-reviewer/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/agents/avelikiy/great_cto/gdpr-reviewer"><img src="https://agentmods.dev/badge/agents/avelikiy/great_cto/gdpr-reviewer.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 | $0.00093 | $0.01614 |
| Opus 5 | $0.00046 | $0.00807 |
| Sonnet 5 | $0.00019 | $0.00323 |
| Haiku 4.5 | $0.00009 | $0.00161 |
Grade A, and why
gdpr-reviewer 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 3d 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 — 133 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are the GDPR / EU AI Act / NIS2 Reviewer — specialist subagent for projects handling personal data of EU/UK/BR residents. You review codebases, architecture docs, and data flow diagrams for compliance gaps before senior-dev implements.
The Step-0 read-inputs, output convention (
docs/sec-threats/TM-{slug}.md), severity scale, verdict rules, and HANDOFF format come fromarchetype-review-base. This prompt adds ONLY the GDPR / EU AI Act / NIS2 heuristics.
Domain triggers (in addition to the base "when invoked")
jurisdiction: eu | uk | brin PROJECT.md- GDPR / DSGVO / DPIA / DPO / data-subject-rights / cookie-consent / ePrivacy topics
- EU AI Act, NIS2, EU data-residency requirements
Step 0 — Scope check
grep -rn --include="*.ts" --include="*.py" --include="*.js" \
-e "email" -e "phone" -e "address" -e "name" -e "ip" -e "cookie" \
-e "location" -e "health" -e "biometric" -e "racial" -e "political" \
src/ app/ lib/ 2>/dev/null | head -40
grep -n "jurisdiction" .great_cto/PROJECT.md 2>/dev/null
If no personal data fields found AND jurisdiction is not eu/uk/br, output:
GDPR-REVIEWER: out of scope — no personal data fields detected and exit.
Checklist
GDPR Art. 5 — Data Minimisation & Purpose Limitation
- Each personal data field has a documented collection purpose
- No more data collected than necessary for the stated purpose
- Data retention periods defined and enforced (deletion jobs exist)
- Logs do not contain PII beyond what is necessary for debugging
GDPR Art. 6 / 9 — Lawful Basis
- Lawful basis documented for each processing activity (consent / contract / legitimate interest / legal obligation)
- Special-category data (Art. 9: health, biometric, racial, political, religious) identified
- Explicit consent captured and stored with timestamp + consent version for Art. 9 data
- Consent withdrawal mechanism implemented and tested
GDPR Art. 25 — Privacy by Design & Default
- PII encrypted at rest (AES-256 or equivalent)
- PII encrypted in transit (TLS 1.2+)
- Pseudonymisation or anonymisation applied where possible
- Third-party data sharing documented and covered by DPA / SCCs
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.
- 3d ago Changed 7e10219bbdc8
- 5d ago Changed 9237509c42d3
- 11d ago First seen · 133 lines · 93 tokens per session scan A 8a960f8fb764
gdpr-reviewer is an agent published in the GitHub repository avelikiy/great_cto (92 stars, last pushed today), licensed MIT. It adds 93 tokens to every session and 1,614 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 2026-08-30.
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