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 agentmods add skills/agentsecops/secopsagentkit/ir-velociraptornpx skills add AgentSecOps/SecOpsAgentKit --skill ir-velociraptorgit clone --depth 1 https://github.com/AgentSecOps/SecOpsAgentKitWrote 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/agentsecops/secopsagentkit/ir-velociraptor)<a href="https://agentmods.dev/skills/agentsecops/secopsagentkit/ir-velociraptor"><img src="https://agentmods.dev/badge/skills/agentsecops/secopsagentkit/ir-velociraptor.svg" alt="Measured on agentmods" 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 | $0.00107 | $0.02753 |
| Opus 5 | $0.00053 | $0.01376 |
| Sonnet 5 | $0.00021 | $0.00551 |
| Haiku 4.5 | $0.00011 | $0.00275 |
Grade C, and why
ir-velociraptor scanned grade C with 1 finding 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 4d 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.
Harvests environment variableshighData exfiltration
Enumerating or grepping the environment for keys collects credentials unrelated to what the mod says it does.
- **Sensitive Data Handling**: VQL queries can collect credentials, PII, and sensitive files. Implement data minimization - only collect necessary evidence. Use encryption for evidence transport and storage. 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 ships with it
12 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.
- assets/.gitkeep 221 B
- assets/artifact-template.yaml 3.5 KB
- assets/ci-config-template.yml 11 KB
- assets/hunt-template.yaml 5.2 KB
- assets/offline-collector-config.yaml 6.7 KB
- assets/rule-template.yaml 11 KB
- references/artifact-development.md 13 KB
- references/deployment-guide.md 15 KB
- references/EXAMPLE.md 15 KB
- references/mitre-attack-mapping.md 15 KB
- references/vql-patterns.md 15 KB
- references/WORKFLOW_CHECKLIST.md 8.2 KB
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.
- 4d ago First seen · 334 lines · 107 tokens per session scan C 0d73e6e09f7b
ir-velociraptor is a skill published in the GitHub repository AgentSecOps/SecOpsAgentKit (202 stars, last pushed 4mo ago), with no licence file. It adds 107 tokens to every session and 2,753 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it C with 1 finding (harvests environment variables). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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