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/smart-entry-pointsgit 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 | $0.00010 | $0.02171 |
| Opus 5 | $0.00005 | $0.01086 |
| Sonnet 5 | $0.00002 | $0.00434 |
| Haiku 4.5 | $0.00001 | $0.00217 |
Grade A, and why
smart-entry-points 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 — 320 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Smart Entry Points - Intelligent Rule Routing System
🎯 Context-Aware Rule Activation
This file defines automatic routing logic for AI assistants to apply the right rules based on work context.
Automatic Context Detection Rules
File Pattern → Rule Mapping
Frontend Development Context
file_patterns:
- "frontend/**/*.tsx"
- "frontend/**/*.ts"
- "frontend/**/*.jsx"
- "frontend/**/*.js"
- "frontend/**/*.css"
- "frontend/**/*.scss"
primary_rule: "@frontend-development-index"
secondary_rules:
- "@nextjs-hydration-prevention" # For React components
- "@react-query-api-integration" # For API calls
- "@component-architecture-patterns" # For component design
- "@ux-workflow-patterns" # For UX work
- "@nextjs-performance-optimization" # For performance
prerequisites:
- "@sprint-lessons-learned" # Always check Sprint 10 lessons
- "@mcp-browser-tools-setup" # Verify MCP setup for frontend work
Backend Development Context
file_patterns:
- "backend/**/*.py"
- "src/**/*.py"
- "**/*api*.py"
- "**/*service*.py"
- "**/*model*.py"
primary_rule: "@backend-development-index"
secondary_rules:
- "@fastapi-dependency-injection" # For API development
- "@api-design-patterns" # For API design
- "@fastapi-microservice-patterns" # For service architecture
- "@ml-service-integration" # For ML services
prerequisites:
- "@sprint-lessons-learned" # Always check Sprint 10 lessons
- "@use-mcp-servers" # For Supabase MCP usage
Database Work Context
file_patterns:
- "**/*.sql"
- "**/migrations/**"
- "**/database/**"
- "**/schemas/**"
primary_rule: "@use-mcp-servers"
focus: "Supabase MCP operations"
secondary_rules:
- "@api-design-patterns" # For data modeling
prerequisites:
- "@sprint-lessons-learned" # Check for database-related lessons
Testing Context
file_patterns:
- "**/*.test.ts"
- "**/*.test.tsx"
- "**/*.test.py"
- "**/*.spec.*"
- "**/tests/**"
primary_rule: "@sprint10-testing-patterns"
secondary_rules:
- "@nextjs-hydration-prevention" # For frontend tests
- "@fastapi-dependency-injection" # For backend tests
- "@mcp-browser-tools-setup" # For MCP testing
prerequisites:
- "@sprint-lessons-learned" # Apply testing lessons learned
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 · 320 lines · 10 tokens per session scan A 5d2539f6142f
smart-entry-points is a cursor rule published in the GitHub repository rm2thaddeus/Pixel_Detective (21 stars, last pushed 7mo ago), licensed MIT. It adds 10 tokens to every session and 2,171 once invoked, about $0.0001 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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