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/rm2thaddeus/pixel_detective/feature-requestgit clone --depth 1 https://github.com/rm2thaddeus/Pixel_DetectiveWhat 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 | $0.00003 | $0.01200 |
| Opus 5 | $0.00002 | $0.00600 |
| Sonnet 5 | $0.00001 | $0.00240 |
| Haiku 4.5 | $0.00000 | $0.00120 |
Grade A, and why
feature-request 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 2d 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 — 97 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Feature Implementation with MCP Integration
Reference: Follow @use-mcp-servers for detailed MCP workflows and best practices
MCP-Enhanced Feature Development Workflow
1. Map Context & Discovery
- Project Structure:
tree -L 4 --gitignore | cat- identify modules/APIs - Existing Patterns: Use
codebase_searchto find similar features and reusable components - Dependencies Analysis: Use
grep_searchfor exact symbol/import matches - Documentation Research: Use Context7 MCP to gather API docs for new libraries/frameworks needed
- Database Schema Review: Use Supabase MCP to understand existing data structures if feature involves data
2. Specify Requirements & Architecture
- Break feature into testable criteria, use cases, and constraints
- Frontend Requirements: Consider UI/UX implications, accessibility standards
- Backend Requirements: Define data models, API endpoints, business logic
- Integration Points: Identify touchpoints with existing systems
- Performance Criteria: Set measurable performance benchmarks
- Documentation Standards: Plan documentation updates per
@use-mcp-serversguidelines
3. Leverage Reusability & Research
- Component Discovery: Use
codebase_searchandgrep_searchto find reusable patterns - Library Integration: Use Context7 MCP to:
- Research best practices for new dependencies
- Find code examples and implementation patterns
- Understand API compatibility and version requirements
- Database Patterns: Use Supabase MCP to identify reusable query patterns and schema structures
- Similar Features: Use GitHub MCP to search project history for related implementations
4. Plan Changes & MCP Strategy
- File Inventory: List all files to edit/create with specific paths
- Cross-Cutting Concerns: Identify impacts on authentication, logging, error handling, testing
- MCP Server Selection: Choose appropriate MCP servers per
@use-mcp-serverstask-based guide:- Frontend Features: Browser Tools + Browser Control MCP for testing/validation
- Backend Features: Supabase MCP for database operations
- API Integration: Context7 MCP for documentation + GitHub MCP for implementation
- Full-Stack Features: Coordinate multiple MCP servers
- Branch Strategy: Plan feature branch creation via GitHub MCP
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.
- 2d ago First seen · 97 lines · 3 tokens per session scan A f09bb9205dbf
feature-request is a cursor rule published in the GitHub repository rm2thaddeus/Pixel_Detective (21 stars, last pushed 6mo ago), licensed MIT. It adds 3 tokens to every session and 1,200 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.
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