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/zackiles/deno-kit/preparegit clone --depth 1 https://github.com/zackiles/deno-kitWhat 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 | $0.01198 |
| Opus 5 | $0.00000 | $0.00599 |
| Sonnet 5 | $0.00000 | $0.00240 |
| Haiku 4.5 | $0.00000 | $0.00120 |
Grade A, and why
prepare 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 yesterday.
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.
This is a copy
100% identical to prepare — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 103 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Steps to Take Before Reasoning
Immediately before you start reasoning about the human’s prompt, perform the following research steps to gather broad context. Collect any information relevant to the prompt or that would help execute on it effectively:
- Search all packages for shared libraries, utilities, and patterns
- Note what can be reused to avoid redundancy.
- Find and note any schemas, models, types, constants, or configuration files
- Collect relevant structured data critical to the function of the codebase and application.
- Locate coding standards and practices
- Identify conventions you must follow for naming, file structure, code formatting, etc.
- Identify existing tooling, scripts, and workflows
- Note any automated processes or frameworks already in place.
- Review overarching CI/CD pipelines and deployment models
- Ensure your contributions align with established build, test, and release processes.
- Check existing versioning and release management practices
- Understand how changes are documented, tagged, and published.
- Assess design patterns, syntax preferences, or stylistic approaches
- Confirm you are imitating the prevailing style unless it is severely flawed.
Use these findings to maintain consistency and preserve the codebase’s cohesiveness.
Rules for Prepping When Proposing a Solution
-
Recall the Research Objective
- Your proposal must fit seamlessly into the existing architecture, leveraging documented patterns and standards.
-
Incorporate Research Findings
- Reuse any shared libraries or utilities discovered in the “Steps to Take Before Reasoning.”
- Respect existing schemas, models, constants, or configurations to avoid conflicts and duplication.
- Align your proposal with established coding and deployment standards so it can pass automated checks.
-
Draft a High-Level Plan
- Provide a concise outline of how the solution should work.
- Highlight any significant performance, security, or maintainability considerations.
- Call out dependencies, tools, or frameworks that will be involved.
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.
- yesterday First seen · 103 lines · 0 tokens per session scan A e1e9ccbc7cb1
prepare is a cursor rule published in the GitHub repository zackiles/deno-kit (3 stars, last pushed 5mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,198 tokens. A static security scan graded it A with 0 findings. It is 100% identical to prepare, differing in 0 lines, and is treated as a copy.
Other cursor rules, from other repositories
development-conventions
Development conventions, code style, and best practices for the Kaneo project.
docs
This file provides guidelines for working with the documentation in the /docs directory.
architecture
Architecture of openapi-to-cli (ocli).
architecture-constraints
GolemBot architecture hard constraints — must check before modifying any src/ code.
app_feature_first_architecture
Feature-first architecture is a design pattern that organizes code by business features rather than technical layers. This approach promotes better maintainability, scalability, and team collaboration by keeping related functionality together and reducing coupling between different parts of the application.
best_practices
Advanced Best Practices covering Error Handling, Environment Variables, Performance, and Accessibility rules.