Awesome Claude Code Toolkit is a curated collection of extensions and configuration for Claude Code, including agents, skills, commands, plugins, hooks, rules, templates, MCP configurations, and companion apps. It is for Claude Code users who want ready-made workflows and integrations for different development tasks. The catalogue add-ons are selected components from this toolkit.
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/rohitg00/awesome-claude-code-toolkitWrote 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/commands/rohitg00/awesome-claude-code-toolkit/security-scan)<a href="https://agentmods.dev/commands/rohitg00/awesome-claude-code-toolkit/security-scan"><img src="https://agentmods.dev/badge/commands/rohitg00/awesome-claude-code-toolkit/security-scan/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/commands/rohitg00/awesome-claude-code-toolkit/security-scan"><img src="https://agentmods.dev/badge/commands/rohitg00/awesome-claude-code-toolkit/security-scan.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 | $0.00024 | $0.00913 |
| Opus 5.5 | $0.00010 | $0.00365 |
| Sonnet 5.5 | $0.00005 | $0.00183 |
| Haiku 4.5 | $0.00002 | $0.00091 |
Grade A, and why
security-scan 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.
How it starts
The opening of the file, as written. The whole thing — 96 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/code-guardian:security-scan
Perform a security-focused scan of the codebase targeting OWASP Top 10 and common vulnerability patterns.
Process
-
Determine the scan scope:
- Default: scan the entire project from the repository root
- If an argument is provided, limit scanning to that path
- Identify the primary language(s) and framework(s) by checking package.json, requirements.txt, go.mod, Cargo.toml, etc.
-
Scan for each vulnerability category:
A01: Broken Access Control
- Search for endpoints missing authentication middleware
- Check for direct object reference patterns where user IDs from request params access resources without ownership verification
- Look for missing CORS configuration or overly permissive origins (
*) - Find routes that expose admin functionality without role checks
A02: Cryptographic Failures
- Grep for weak hashing algorithms: MD5, SHA1 used for passwords or tokens
- Check for hardcoded encryption keys, salts, or initialization vectors
- Look for HTTP URLs where HTTPS should be used (API calls, webhooks)
- Verify that sensitive data in logs is masked or redacted
A03: Injection
- Search for string concatenation or template literals in SQL queries
- Check for unsanitized input in shell exec, spawn, or system calls
- Look for innerHTML assignments, dangerouslySetInnerHTML without sanitization
- Find regex patterns vulnerable to ReDoS (catastrophic backtracking)
A04: Insecure Design
- Check for missing rate limiting on authentication endpoints
- Look for predictable resource IDs (sequential integers for sensitive resources)
- Verify that file uploads validate type, size, and content
- Check for missing CSRF protection on state-changing requests
A05: Security Misconfiguration
- Search for debug mode enabled in production configs
- Check for default credentials in config files or environment examples
- Look for overly verbose error messages that leak stack traces
- Verify security headers (CSP, X-Frame-Options, HSTS) in server config
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 · 96 lines · 24 tokens per session scan A 598aa9fdcaab
security-scan is a command published in the GitHub repository rohitg00/awesome-claude-code-toolkit (2,717 stars, last pushed 5mo ago), licensed Apache-2.0. It adds 24 tokens to every session and 913 once invoked, about $0.0001 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 2026-09-03.
Other commands, from other repositories
cc-refactor
(Conductor) Refactor a file or module for clarity and simplicity.
create-prompt
Create a new prompt that another Claude can execute.
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.