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 evgenii-studitskikh/Claude-Code-SaaS-Studio --skill compliance-checkgit clone --depth 1 https://github.com/evgenii-studitskikh/Claude-Code-SaaS-StudioWrote 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/evgenii-studitskikh/claude-code-saas-studio/compliance-check)<a href="https://agentmods.dev/skills/evgenii-studitskikh/claude-code-saas-studio/compliance-check"><img src="https://agentmods.dev/badge/skills/evgenii-studitskikh/claude-code-saas-studio/compliance-check/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/evgenii-studitskikh/claude-code-saas-studio/compliance-check"><img src="https://agentmods.dev/badge/skills/evgenii-studitskikh/claude-code-saas-studio/compliance-check.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 | $0.00038 | $0.00721 |
| Opus 5 | $0.00019 | $0.00360 |
| Sonnet 5 | $0.00008 | $0.00144 |
| Haiku 4.5 | $0.00004 | $0.00072 |
Grade A, and why
compliance-check 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 9d 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 — 22 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Prevent the common mistake of shipping a SaaS with real user data before the minimum legal and trust foundations are in place. By reading the PRD, architecture, and data-model docs, the skill builds an inventory of every data item collected or stored, flags which items are PII, traces where each item lives (Supabase, Stripe, Vercel, or a third party), and checks whether the app has the policy documents and code paths needed to honor GDPR data-subject rights (export and delete). It then scores each compliance item as PASS or GAP and produces a prioritized list of the open gaps to close before onboarding real users. Non-autonomous: drafts are presented and require explicit approval before any file is written.
Phases
- Load context — read
docs/specs/prd.mdanddocs/specs/architecture.md; also readdocs/specs/data-model.mdif it exists. If the PRD is missing, stop and direct the user to/write-prd. Extract what data the app collects, from whom, and for what purpose. - Data inventory — build a table of every data item collected or stored, with columns: Item, Is PII (yes/no), Storage location (Supabase / Stripe / Vercel / other), Retention period (known or TBD). Present the table to the user for corrections and additions before proceeding.
- Policies & rights — check for the presence of: (a) a privacy policy stub and Terms of Service; (b) a DPA / subprocessors list covering at minimum Supabase, Stripe, and Vercel; (c) a data-export path that lets a user or tenant download their data; (d) a data-deletion path that removes or anonymizes PII on request; (e) cookie consent if any tracking cookies are used; (f) (SOC 2-lite) an audit trail — key events (authentication, billing changes, and destructive admin actions) are logged to a tamper-evident log or append-only
audit_eventstable. For each item, mark PASS (exists and adequate), GAP (missing or incomplete), or N/A (not applicable). Underfullreview, confirm each item with the user; underlean, present the full checklist and confirm once; undersolo, write then summarize. - Draft — fill
.claude/templates/compliance.mdintodocs/specs/compliance.mdwith the data inventory table and the PASS/GAP checklist. Present the draft and await explicit approval before writing the file. - Verdict — list all open GAPs in priority order (blocking: items that affect real-user data handling; important: items needed before public launch; advisory: best-practice items). Make clear which GAPs must be closed before the app can handle real user data.
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.
- 9d ago First seen · 22 lines · 38 tokens per session scan A f387574c76bf
compliance-check is a skill published in the GitHub repository evgenii-studitskikh/Claude-Code-SaaS-Studio (1 stars, last pushed 2mo ago), licensed MIT. It adds 38 tokens to every session and 721 once invoked, about $0.0002 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 2026-08-31.
Other skills, from other repositories
consent
A consent manager for allowing or withdrawing permission to process learning and behavior data. Consent means a person actively agrees to this data use.
compliance-check
Validate codebase against code-level compliance signals for regulatory frameworks (FedRAMP, FIPS, OWASP, SOC 2). Scoped to source code analysis only — not a compliance certification.
themis
A code-based privacy policy drafting workflow. It checks where a project collects, stores, sends, or deletes personal information and uses only findings supported by file-and-line evidence.
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PASS/FAIL/N/A checklist for the high-risk AI obligations under Articles 8-15 of the EU AI Act, plus the quality management system, conformity assessment, registration, post-market monitoring, and incident reporting.
EU AI Act Risk Classification
Decision tree for classifying an AI system into the EU AI Act risk tier (unacceptable/high/limited/minimal) and identifying the actor role (provider/deployer/importer/distributor).