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 rules/ctxs-ai/ctxs.ai/agentgit clone --depth 1 https://github.com/ctxs-ai/ctxs.aiWrote 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/rules/ctxs-ai/ctxs.ai/agent)<a href="https://agentmods.dev/rules/ctxs-ai/ctxs.ai/agent"><img src="https://agentmods.dev/badge/rules/ctxs-ai/ctxs.ai/agent.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 | $0.00000 | $0.00281 |
| Opus 5 | $0.00000 | $0.00140 |
| Sonnet 5 | $0.00000 | $0.00056 |
| Haiku 4.5 | $0.00000 | $0.00028 |
Grade A, and why
agent 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 4d 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.
What it actually says
This is an agent implementation that will serve as an intelligent librarian, organizing and managing information in markdown files. The implementation uses Mastra as its foundation.
Key Architectural Points:
- The agent is implemented as a TypeScript application using Bun as the runtime
- Core functionality is centered around markdown file processing and LLM interactions
- Uses Commander.js for CLI interface design
- Implements frontmatter validation and generation capabilities
Development Guidelines:
- Keep the agent's core responsibilities separate from the file processing logic
- Use TypeScript types rigorously, especially for frontmatter and configuration interfaces
- Maintain clear separation between:
- Agent core logic
- File system operations
- LLM interactions
- CLI interface
When implementing new features:
- Consider the agent's primary role as a librarian/organizer
- Ensure proper error handling for file operations and LLM interactions
- Add appropriate logging for debugging and monitoring
- Keep the CLI interface intuitive and consistent
Code Style:
- Use async/await for asynchronous operations
- Implement proper TypeScript types for all functions and data structures
- Document complex logic with clear comments
- Use meaningful variable names that reflect the librarian/organizer domain
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.
- 4d ago First seen · 33 lines · 0 tokens per session scan A 7e7ac3a12025
agent is a cursor rule published in the GitHub repository ctxs-ai/ctxs.ai (27 stars, last pushed 1y ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 281 tokens. 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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