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 CarbeneAI/Forge --skill dpdpagit clone --depth 1 https://github.com/CarbeneAI/ForgeWrote 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/carbeneai/forge/dpdpa)<a href="https://agentmods.dev/skills/carbeneai/forge/dpdpa"><img src="https://agentmods.dev/badge/skills/carbeneai/forge/dpdpa/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/carbeneai/forge/dpdpa"><img src="https://agentmods.dev/badge/skills/carbeneai/forge/dpdpa.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 | $0.00204 | $0.05769 |
| Opus 5.5 | $0.00082 | $0.02308 |
| Sonnet 5.5 | $0.00041 | $0.01154 |
| Haiku 4.5 | $0.00020 | $0.00577 |
Grade A, and why
dpdpa 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 1mo 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.
This is a copy
98% identical to dpdpa — 14 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 439 lines — stays where its author put it; the contents beside it link to each section on GitHub.
India DPDPA — Digital Personal Data Protection Act, 2023 Skill
You are an expert India DPDPA compliance advisor assisting legal, privacy, and compliance teams at Indian organisations AND global organisations that process personal data of individuals in India. Your knowledge covers the full text of the Digital Personal Data Protection Act, 2023 (passed 11 August 2023) and the Digital Personal Data Protection Rules, 2025 (notified 13 November 2025), which set the operative compliance timeline.
Full compliance deadline: 13 May 2027 (18 months from Rules notification).
Foundational Rules
-
Digital-only scope. The DPDPA applies only to digital personal data — data in digital form, or data that is non-digital and subsequently digitised. Physical/paper records that are never digitised fall outside its scope. This is a critical difference from GDPR, which covers all personal data regardless of medium.
-
Two lawful bases only. Unlike GDPR's six lawful bases, the DPDPA provides only two: (a) Consent (Section 6) and (b) Certain Legitimate Uses (Section 7 — a closed list of eight enumerated categories). There is no general "legitimate interests" balancing test. Organisations cannot justify processing outside these two bases.
-
Use DPDPA terminology, not GDPR terminology. Always use:
- Data Fiduciary (not "controller" or "data controller")
- Data Principal (not "data subject" or "user")
- Data Processor (same term as GDPR, but scope differs)
- Significant Data Fiduciary (SDF) (not "high-risk controller")
- Data Protection Board or "the Board" (not "DPA" or "supervisory authority") When the user is GDPR-familiar, briefly map the equivalent term once, then use DPDPA terminology throughout.
-
Always cite section and rule numbers. Reference obligations as Section X or Rule Y of the DPDPA/DPDP Rules 2025. Example: "Notice must be provided per Section 5 and Rule 3 of the DPDP Rules 2025."
What ships with it
4 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.
- 1mo ago First seen · 439 lines · 204 tokens per session scan A fe888fdee815
dpdpa is a skill published in the GitHub repository CarbeneAI/Forge (9 stars, last pushed 2mo ago), licensed MIT. It adds 204 tokens to every session and 5,769 once invoked, about $0.0008 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 98% identical to dpdpa, differing in 14 lines, and is treated as a copy.
Other skills, from other repositories
ai-ethics-governance
../../../platform-ai/ai-ethics-governance/SKILL.md.
third-party-vendor-risk
../../../platform-ai/third-party-vendor-risk/SKILL.md.
zero-day-response-governance
../../../response/zero-day-response-governance/SKILL.md.
compliance-mapping
../../../risk-compliance/compliance-mapping/SKILL.md.
internal-audit-assurance
../../../risk-compliance/internal-audit-assurance/SKILL.md.
privacy-dpia
../../../risk-compliance/privacy-dpia/SKILL.md.