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 zey-2/security_skillpacks --skill mandate-2-3-4-runtime-evidence-intake-guidegit clone --depth 1 https://github.com/zey-2/security_skillpacksWrote 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/zey-2/security_skillpacks/mandate-2-3-4-runtime-evidence-intake-guide)<a href="https://agentmods.dev/skills/zey-2/security_skillpacks/mandate-2-3-4-runtime-evidence-intake-guide"><img src="https://agentmods.dev/badge/skills/zey-2/security_skillpacks/mandate-2-3-4-runtime-evidence-intake-guide/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/zey-2/security_skillpacks/mandate-2-3-4-runtime-evidence-intake-guide"><img src="https://agentmods.dev/badge/skills/zey-2/security_skillpacks/mandate-2-3-4-runtime-evidence-intake-guide.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 | $0.00061 | $0.00669 |
| Opus 5.5 | $0.00024 | $0.00268 |
| Sonnet 5.5 | $0.00012 | $0.00134 |
| Haiku 4.5 | $0.00006 | $0.00067 |
Grade A, and why
mandate-2-3-4-runtime-evidence-intake-guide 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 2mo 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.
The source is not reproduced here
No licence file
A repository with no LICENSE is all rights reserved by default, so the body is not copied here. The metadata, the measurements and the link are.
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.
- 2mo ago First seen · 72 lines · 61 tokens per session scan A 8112447415d1
mandate-2-3-4-runtime-evidence-intake-guide is a skill published in the GitHub repository zey-2/security_skillpacks (5 stars, last pushed 8mo ago), with no licence file. It adds 61 tokens to every session and 669 once invoked, about $0.0002 per session on Opus 5.5. 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
prowler-compliance
Creates, syncs, audits and maintains Prowler compliance frameworks: universal multi-provider JSON (preferred) and legacy per-provider JSON, ConfigRequirements guardrails, output formatters, external compliance plug-ins (entry points), and check-to-requirement mapping audits. Trigger: When working with compliance…
policy
Define and enforce decision policies, compliance rules, and exceptions over Semantica graphs. Uses ContextGraph.checkdecisionrules/enforcedecisionpolicy and context.PolicyEngine.
ai-ethics-review
Conduct a structured ethical review of an AI or ML feature, model, or product. Use when preparing to deploy an AI system, assessing algorithmic risk, auditing a model for bias, or producing a responsible AI impact assessment. Produces a structured ethics review covering fairness, transparency, privacy, safety…
open-weights
Use when choosing an open-weight LLM and clearing it for use — which family and size fit the task, the hardware and the budget, and above all whether the license permits shipping. Owns the license-class map (OSI-open versus custom-community versus non-commercial), the always-verify-the-model-card rule, size-to-VRAM…
813-regulations-iso-42001
Use when reviewing, designing, or modifying Java enterprise systems that use GenAI, LLMs, AI-assisted coding, RAG, AI agents, generated code, generated dependencies, prompt workflows, external model providers, or AI-enabled business logic and need ISO/IEC 42001 AI management system-aware engineering guidance. Part of…
801-regulations-eu-ai-act
Use when reviewing, designing, or modifying Java enterprise systems that use AI, LLMs, AI agents, RAG, tool calling, workflow automation, or model-based decision support and need EU AI Act regulatory awareness. This should trigger for requests such as Review a Java AI system for EU AI Act controls; Design governance…