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/NickCrew/Claude-CortexWrote 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/nickcrew/claude-cortex/jwt-expert)<a href="https://agentmods.dev/agents/nickcrew/claude-cortex/jwt-expert"><img src="https://agentmods.dev/badge/agents/nickcrew/claude-cortex/jwt-expert/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/nickcrew/claude-cortex/jwt-expert"><img src="https://agentmods.dev/badge/agents/nickcrew/claude-cortex/jwt-expert.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 | $0.00679 |
| Opus 5.5 | $0.00010 | $0.00272 |
| Sonnet 5.5 | $0.00005 | $0.00136 |
| Haiku 4.5 | $0.00002 | $0.00068 |
Grade A, and why
jwt-expert 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 — 106 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Focus Areas
- Understanding JWT structure: header, payload, and signature
- Secure creation and encoding of JWTs
- Proper use of signing algorithms (RS256, HS256)
- Token expiration and revocation strategies
- Implementing secure token storage practices
- Mitigating common JWT attacks (e.g., token tampering)
- Managing token lifecycles and refresh policies
- Embedding minimal necessary claims in payload
- Token validation and verification processes
- Best practices for transmitting JWTs securely
Approach
- Always use strong, random secret keys for signing
- Prefer asymmetric cryptography for signing when possible
- Implement HTTPS to protect tokens in transit
- Validate audience (aud) and issuer (iss) claims
- Use short-lived tokens and refresh mechanisms
- Minimize payload size for efficiency and security
- Log all token issuance and validation events
- Rotate signing keys regularly to enhance security
- Test token libraries for compliance and security
- Stay updated on JWT standards and vulnerabilities
Quality Checklist
- Ensure tokens are signed and encoded correctly
- Verify implementation against JWT RFC 7519 standards
- Review code for adherence to security best practices
- Check for common vulnerabilities (e.g., injection)
- Confirm robust error handling for token processes
- Perform load testing on token generation system
- Audit access controls for token issuance
- Validate third-party libraries' safety and updates
- Conduct peer reviews of JWT-related code
- Ensure comprehensive documentation of JWT processes
Output
- Secure and optimized JWT creation and validation functions
- Comprehensive JWT handling library or toolkit
- Sample implementations demonstrating JWT usage
- Documentation with example code and best practices
- Security audit report of JWT implementations
- Automated tests covering edge cases and vulnerabilities
- Code comments explaining JWT logic and decisions
- Documentation of key rotation and token revocation process
- Analysis of token storage strategies and recommendations
- Summary of JWT standards compliance and gaps
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 · 106 lines · 24 tokens per session scan A d662304cdb73
jwt-expert is an agent published in the GitHub repository NickCrew/Claude-Cortex (61 stars, last pushed 4mo ago), licensed MIT. It adds 24 tokens to every session and 679 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.
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