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/ersinkoc/security-check/sc-verifiernpx skills add ersinkoc/security-check --skill sc-verifiergit clone --depth 1 https://github.com/ersinkoc/security-checkWrote 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/ersinkoc/security-check/sc-verifier)<a href="https://agentmods.dev/skills/ersinkoc/security-check/sc-verifier"><img src="https://agentmods.dev/badge/skills/ersinkoc/security-check/sc-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 | $0.00014 | $0.02011 |
| Opus 5 | $0.00007 | $0.01006 |
| Sonnet 5 | $0.00003 | $0.00402 |
| Haiku 4.5 | $0.00001 | $0.00201 |
Grade A, and why
sc-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 5d 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.
How it starts
The opening of the file, as written. The whole thing — 228 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SC: Verifier — False Positive Elimination & Confidence Scoring
Purpose
The verifier skill processes all raw findings from Phase 2 vulnerability skills, eliminates false positives through multi-criteria analysis, assigns confidence scores, merges duplicate findings, and produces a curated list of verified security issues. This is the quality gate that ensures the final report contains actionable, high-signal findings.
Activation
Runs in Phase 3 of the pipeline, after all Phase 2 vulnerability skills have completed.
Input
All files matching security-report/*-results.md
Output
File: security-report/verified-findings.md
Verification Process
Step 1: Finding Collection
- Read all
*-results.mdfiles fromsecurity-report/ - Parse each finding into a structured format (title, severity, confidence, file, line, type, description)
- Skip files containing "No issues found"
- Create a unified finding list with source skill attribution
Step 2: Reachability Analysis
For each finding, determine if the vulnerable code is actually reachable:
Check if code is in an executable path:
- Is the file imported/included by any other file?
- Is the function called from an entry point (HTTP handler, CLI command, etc.)?
- Is the file part of the build output (not excluded by build config)?
- Trace the call chain from entry point to vulnerable code
Reachability scoring:
- Directly reachable from HTTP handler: +30 confidence
- Reachable through 1-2 function calls: +20 confidence
- Reachable through 3+ function calls: +10 confidence
- No clear call path found: -20 confidence
- Dead code (no imports/calls): -40 confidence
Step 3: Sanitization Check
For each finding involving user input, check if input is sanitized:
Sanitization indicators:
- Input passes through validation library (Zod, Joi, Pydantic, Bean Validation)
- Input is parameterized (prepared statements, ORM methods)
- Input passes through encoding/escaping function (htmlspecialchars, html/template, DOMPurify)
- Input is type-cast to safe type (parseInt, strconv.Atoi)
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.
- 5d ago First seen · 228 lines · 14 tokens per session scan A f33e7a9c4260
sc-verifier is a skill published in the GitHub repository ersinkoc/security-check (56 stars, last pushed 1mo ago), licensed MIT. It adds 14 tokens to every session and 2,011 once invoked, about $0.0001 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 2026-08-30.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
next-cache-components-optimizer
Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…
next-partial-prefetching-adoption
Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…
chronicle
Analyze Copilot session history for standup reports, usage tips, session search, and session reindexing. Use when the user asks for a standup, daily summary, usage tips, workflow recommendations, wants to search or find past sessions by keyword/file/PR, wants to reindex their session store, or asks about deleting…