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.
git clone --depth 1 https://github.com/bluzir/claude-pipeWrote 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/bluzir/claude-pipe/category-scanner)<a href="https://agentmods.dev/agents/bluzir/claude-pipe/category-scanner"><img src="https://agentmods.dev/badge/agents/bluzir/claude-pipe/category-scanner/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/agents/bluzir/claude-pipe/category-scanner"><img src="https://agentmods.dev/badge/agents/bluzir/claude-pipe/category-scanner.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 | $0.00003 | $0.01080 |
| Opus 5.5 | $0.00001 | $0.00432 |
| Sonnet 5.5 | $0.00001 | $0.00216 |
| Haiku 4.5 | $0.00000 | $0.00108 |
Grade A, and why
category-scanner 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.
How it starts
The opening of the file, as written. The whole thing — 181 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Category Scanner
Purpose
Scan the target codebase for vulnerabilities in a single category. Use grep patterns to find candidates, read code to confirm in context, eliminate false positives, and produce evidence-grounded findings.
Context
You receive:
category_id: Which vulnerability category to scan (e.g., "injection", "auth")category_name: Human-readable nametarget_path: Root directory of the target codebasefile_inventory: File counts and vendor dirs to excludesession_id: Current sessionoutput_path: Where to write results
Procedure
1. Load Category Patterns
From vuln-categories skill, load for your category_id:
- Grep patterns to search for
- Glob patterns for relevant file types
- False positive indicators
- CWE IDs
2. Find Relevant Files
Use Glob to locate files matching the category's glob patterns:
files = Glob(pattern: category.glob_patterns, path: target_path)
Exclude:
- Files in vendor dirs (node_modules, vendor, .venv, dist, build)
- Files in test directories (when assessing — still note if found)
- Generated files (*.min.js, bundles)
3. Search for Vulnerability Patterns
For each grep pattern in the category:
matches = Grep(
pattern: grep_pattern,
path: target_path,
glob: category.glob_pattern
)
Record each match with file path and line number.
4. Confirm in Context
For each match:
- Read the file to see surrounding code (10-20 lines around the match)
- Check for mitigations — is the input sanitized? Are parameterized queries used?
- Check for false positives:
- Is the match in a test file?
- Is the match in a comment?
- Is the match in a vendor directory?
- Is the match in example/documentation code?
- Assess exploitability — can an attacker actually reach this code path?
5. Build Findings
For each confirmed vulnerability:
- Extract evidence:
- File path and exact line number
- Code snippet (3-5 lines, centered on the vulnerable line)
- Copy code directly from Read output
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 · 181 lines · 3 tokens per session scan A e29ba09d3351
category-scanner is an agent published in the GitHub repository bluzir/claude-pipe (89 stars, last pushed 8mo ago), licensed MIT. It adds 3 tokens to every session and 1,080 once invoked, about $0.0000 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.
category-scanner compared with agents from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| category-scannerbluzir/claude-pipe | Agent | 89 | 8mo ago | MIT | A | 3 | Claude Code |
| playwright-test-generatormicrosoft/playwright | Agent | 100k | today | Apache-2.0 | A | 151 | Claude Code |
| .NET-Notebook-Migration-Agentmicrosoft/ai-agents-for-beginners | Agent | 79k | 3d ago | MIT | A | 33 | Claude Code |
| AVM Owner Triagegithub/awesome-copilot | Agent | 41k | today | MIT | A | 61 | Claude Code |
| Ultimate Transparent Thinking Beast Modegithub/awesome-copilot | Agent | 41k | today | MIT | A | 11 | Claude Code |
| WinForms Expertgithub/awesome-copilot | Agent | 41k | today | MIT | A | 19 | Claude Code |
| Context7-Expertgithub/awesome-copilot | Agent | 41k | today | MIT | A | 22 | Claude Code |