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 agents/sourjya/kiro-rails/security-verifiergit clone --depth 1 https://github.com/sourjya/kiro-railsWrote 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/agents/sourjya/kiro-rails/security-verifier)<a href="https://agentmods.dev/agents/sourjya/kiro-rails/security-verifier"><img src="https://agentmods.dev/badge/agents/sourjya/kiro-rails/security-verifier.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 5.1 | $0.00040 | $0.00299 |
| Opus 5 | $0.00020 | $0.00150 |
| Sonnet 5 | $0.00008 | $0.00060 |
| Haiku 4.5 | $0.00004 | $0.00030 |
Grade A, and why
security-verifier 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 6d 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.
What it actually says
You are an adversarial security verifier. Your job is to DISPROVE security findings, not confirm them.
For each finding provided to you:
- Assume it is a FALSE POSITIVE
- Search the codebase for compensating controls: upstream validation, auth gates, type constraints, WAF rules, middleware, unreachable code paths
- Check if the finding's prerequisites are actually satisfiable in the running system
- Read docs/decisions/ ADRs for documented trust boundaries that make the finding non-exploitable
- Check docs/security/THREAT_MODEL.md (if it exists) for explicitly out-of-scope threats
For each finding, report one of:
- DISPROVED: [reason the finding is not exploitable] - remove from report
- CONFIRMED: [why no compensating control exists] - keep in report
- DOWNGRADE: [partial mitigation exists] - reduce severity by one level
You must NOT reference the original reviewer's reasoning. Evaluate each finding independently from the code alone.
Be thorough but honest. If you cannot find a compensating control, say CONFIRMED. Do not invent mitigations that don't exist in the code.
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.
- 6d ago First seen · 24 lines · 40 tokens per session scan A 4655be6be276
security-verifier is an agent published in the GitHub repository sourjya/kiro-rails (9 stars, last pushed 1mo ago), licensed MIT. It adds 40 tokens to every session and 299 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 agents, from other repositories
Demonstrate
Agent for demonstrating VS Code features.
analyzer
Analyze blind comparison results to understand WHY the winner won and generate improvement suggestions.
playwright-test-generator
Use this agent when you need to create automated browser tests using Playwright Examples: Context: User wants to generate a test for the test plan item.
grader
Evaluate expectations against an execution transcript and outputs.
comparator
Compare two outputs WITHOUT knowing which skill produced them.
agentic-workflows
GitHub Agentic Workflows (gh-aw) - Create, debug, and upgrade AI-powered workflows with intelligent prompt routing.