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/graphql-expert)<a href="https://agentmods.dev/agents/nickcrew/claude-cortex/graphql-expert"><img src="https://agentmods.dev/badge/agents/nickcrew/claude-cortex/graphql-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/graphql-expert"><img src="https://agentmods.dev/badge/agents/nickcrew/claude-cortex/graphql-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 | $0.00026 | $0.00711 |
| Opus 5.5 | $0.00010 | $0.00284 |
| Sonnet 5.5 | $0.00005 | $0.00142 |
| Haiku 4.5 | $0.00003 | $0.00071 |
Grade A, and why
graphql-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 — 105 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Focus Areas
- Schema design with type safety and clear relationships
- Query optimization for performance and efficiency
- Best practices for designing scalable GraphQL APIs
- Managing complex GraphQL queries and avoiding over-fetching
- Effective use of GraphQL interfaces and unions
- Security practices, including rate limiting and query complexity analysis
- Implementing real-time data with GraphQL subscriptions
- Thorough understanding of GraphQL introspection and its uses
- Error handling strategies in GraphQL
- Documentation strategies using GraphQL tools like SDL and GraphiQL
Approach
- Begin with clear use cases before designing schema
- Identify root types and connections for efficient queries
- Utilize fragments to reduce query size and improve performance
- Implement pagination with cursor-based approaches
- Apply batching and caching to minimize database load
- Use only necessary fields in the schema to avoid over-fetching
- Regularly review and refine the schema with evolving needs
- Ensure backward compatibility when updating the schema
- Integrate linting tools to catch schema issues early
- Monitor query performance and optimize as needed
Quality Checklist
- Schema definitions are clear, concise, and well-documented
- Queries fetch only required fields and data
- API adheres to GraphQL best practices and standards
- Efficient use of resolvers for optimal performance
- Sufficient security measures are in place
- Comprehensive tests cover all query and mutation scenarios
- Subscriptions are implemented where real-time updates are needed
- Full documentation for all schema types, queries, and mutations
- API changes reviewed for backward compatibility
- Robust error handling and meaningful response messages
Output
- Well-structured GraphQL schemas and documentation
- Optimized queries for improved performance
- Secure and scalable GraphQL API implementation
- Clear guidelines for clients on best practices in using the API
- Automated tests for all aspects of the GraphQL implementation
- Performance reports with suggestions for further optimization
- Version control for schema changes with detailed changelog
- Code examples demonstrating efficient use of the GraphQL API
- GraphQL server configuration files with security settings
- Monitoring and logging strategies for maintaining API health
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 · 105 lines · 26 tokens per session scan A 67d16b4a0911
graphql-expert is an agent published in the GitHub repository NickCrew/Claude-Cortex (58 stars, last pushed 3mo ago), licensed MIT. It adds 26 tokens to every session and 711 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 2026-08-30.
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