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/holasoymalva/AI-PR-Reviewer-TasksWrote 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/holasoymalva/ai-pr-reviewer-tasks/analyze-pr-changes)<a href="https://agentmods.dev/rules/holasoymalva/ai-pr-reviewer-tasks/analyze-pr-changes"><img src="https://agentmods.dev/badge/rules/holasoymalva/ai-pr-reviewer-tasks/analyze-pr-changes/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/rules/holasoymalva/ai-pr-reviewer-tasks/analyze-pr-changes"><img src="https://agentmods.dev/badge/rules/holasoymalva/ai-pr-reviewer-tasks/analyze-pr-changes.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 | $0.00007 | $0.01254 |
| Opus 5 | $0.00003 | $0.00627 |
| Sonnet 5 | $0.00001 | $0.00251 |
| Haiku 4.5 | $0.00001 | $0.00125 |
Grade A, and why
analyze-pr-changes 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 9d 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 — 174 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Rule: Analyze Pull Request Changes
Goal
To guide an AI assistant in performing a comprehensive analysis of Pull Request changes, identifying impact, potential issues, and areas requiring attention during code review.
Process
-
Receive PR Context: The user provides changed files using @ tags and optional context about the PR purpose.
-
Initial Analysis: Examine all provided files to understand:
- Scope and nature of changes
- Files modified, added, or deleted
- Overall impact on the codebase
- Dependencies affected
-
Ask Clarifying Questions: Gather additional context if needed:
- PR Purpose: "What is the main goal of this PR? (feature, bugfix, refactor, etc.)"
- Breaking Changes: "Are there any intended breaking changes or API modifications?"
- Dependencies: "Are there new dependencies or version updates involved?"
- Testing: "What testing has been done for these changes?"
- Deployment: "Are there any deployment considerations or environment changes?"
-
Systematic Analysis: Perform detailed analysis across multiple dimensions.
-
Generate Report: Create a comprehensive analysis report with findings and recommendations.
Analysis Framework
1. Change Scope Analysis
- Files Changed: Count and categorize modified files
- Lines of Code: Estimate addition/deletion/modification scope
- Change Type: Feature, bugfix, refactor, documentation, configuration
- Impact Radius: How many parts of the system are affected
2. Architectural Impact Assessment
- Design Patterns: Changes to existing patterns or introduction of new ones
- Code Structure: Impact on module organization and dependencies
- API Changes: Modifications to public interfaces or contracts
- Database Changes: Schema modifications, migrations, or query changes
- Configuration: Changes to environment variables, settings, or deployment configs
3. Security Analysis
- Authentication/Authorization: Changes to access control or user management
- Input Validation: Proper sanitization and validation of user inputs
- Data Exposure: Risk of sensitive data leakage or exposure
- Dependency Security: New packages or version updates with security implications
- OWASP Compliance: Adherence to common security best practices
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.
- 9d ago First seen · 174 lines · 7 tokens per session scan A c4fa78331304
analyze-pr-changes is a cursor rule published in the GitHub repository holasoymalva/AI-PR-Reviewer-Tasks (14 stars, last pushed 1y ago), licensed Apache-2.0. It adds 7 tokens to every session and 1,254 once invoked, about $0.0000 per session on Opus 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.
Other cursor rules, from other repositories
refactoring
Refactoring: systematic approach, extract/inline, guard clauses, early returns.
clean-code
Clean code: naming, functions, simplicity.
code-review
Code review: reviewing approach, authoring PRs, feedback conventions.
git-workflow
Git workflow: commits, branches, PRs, history management.
refactor-test
Review and refactor generated unit tests for improved quality and coverage.
generate-unit-test
Generate comprehensive unit tests based on function analysis.