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 Factory-AI/factory-plugins --skill vulnerability-validationgit clone --depth 1 https://github.com/Factory-AI/factory-pluginsWrote 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/factory-ai/factory-plugins/vulnerability-validation)<a href="https://agentmods.dev/skills/factory-ai/factory-plugins/vulnerability-validation"><img src="https://agentmods.dev/badge/skills/factory-ai/factory-plugins/vulnerability-validation/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/factory-ai/factory-plugins/vulnerability-validation"><img src="https://agentmods.dev/badge/skills/factory-ai/factory-plugins/vulnerability-validation.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 | $0.00040 | $0.02473 |
| Opus 5.5 | $0.00016 | $0.00989 |
| Sonnet 5.5 | $0.00008 | $0.00495 |
| Haiku 4.5 | $0.00004 | $0.00247 |
Grade A, and why
vulnerability-validation 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.
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
1 file 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 · 312 lines · 40 tokens per session scan A 9760a3063ffc
vulnerability-validation is a skill published in the GitHub repository Factory-AI/factory-plugins (115 stars, last pushed 9d ago), with no licence file. It adds 40 tokens to every session and 2,473 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 2026-08-30.
Other skills, from other repositories
smiles-validation
Strict SMILES validation, structural comparison, and modification verification. Catches invalid LLM-generated molecules.
hypothesis-testing
Applies the scientific method to debugging by helping users form specific, testable hypotheses, design targeted experiments, and systematically confirm or reject theories to find root causes. Use when a user says their code isn't working, they're getting an error, something broke, they want to troubleshoot a bug, or…
proof-of-work
Proof artifact generation patterns for task validation. Covers screenshots, test results, deployments, and confidence scoring.
error-handling
Implement robust error handling with custom error types, proper propagation, user-friendly messages, and logging. Use when adding error handling to APIs, libraries, or applications.
context-verifier
Know the file you're editing is the file you think it is — verify integrity before you act.
Golden Master
Track source-of-truth relationships between files — know when derived content becomes stale.