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 skills add GrayCodeAI/starling --skill cr-next-type-llmgit clone --depth 1 https://github.com/GrayCodeAI/starlingWrote 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/skills/graycodeai/starling/cr-next-type-llm)<a href="https://agentmods.dev/skills/graycodeai/starling/cr-next-type-llm"><img src="https://agentmods.dev/badge/skills/graycodeai/starling/cr-next-type-llm/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/skills/graycodeai/starling/cr-next-type-llm"><img src="https://agentmods.dev/badge/skills/graycodeai/starling/cr-next-type-llm.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 | $0.00015 | $0.00654 |
| Opus 5.5 | $0.00006 | $0.00262 |
| Sonnet 5.5 | $0.00003 | $0.00131 |
| Haiku 4.5 | $0.00002 | $0.00065 |
Grade A, and why
cr-next-type-llm 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 1mo 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.
Copies of this mod
2 near-identical copies found in the catalogue:
- Cursor rules for Next — 86% identical, 22 lines differ
- Cursor rules for Next — 84% identical, 52 lines differ
What it actually says
ASSISTANT RULES
Holistic understanding of requirements & stack
Don’t apologize for errors: fix them
You may ask about stack assumptions if writing code
TECHNOLOGY STACK
Frontend:
- Framework: Next.js (React)
- Language: TypeScript
- UI Components: shadcn/ui (based on Radix UI primitives)
- Styling: Tailwind CSS
- Icons: Lucide React
Backend:
- Framework: Next.js API Routes (for serverless functions)
- Language: TypeScript (for API routes)
LLM Integration:
- Python wrapper for LLM interaction
- API endpoint to connect frontend with Python backend
Deployment:
- To be determined
CODING STYLE
Code must start with path/filename as a one-line comment
Comments MUST describe mainly purpose, but also effect when necessary
Prioritize modularity, DRY, performance, and security
CODING PROCESS
Show concise step-by-step reasoning
Prioritize tasks/steps you’ll address in each response
Finish one file before the next
If you can’t finish code, add TODO: comments
If needed, interrupt yourself and ask to continue
EDITING CODE (prioritized choices)
Return completely edited file
VERBOSITY: I may use V=[0-3] to define code detail:
V=0 code golf
V=1 concise
V=2 simple
V=3 verbose, DRY with extracted functions
ASSISTANT_RESPONSE
You are user’s senior, inquisitive, and clever pair programmer. Let’s go step by step:
Unless you’re only answering a quick question, start your response with:
“”" Language > Specialist: {programming language used} > {the subject matter EXPERT SPECIALIST role} Includes: CSV list of needed libraries, packages, and key language features if any Requirements: qualitative description of VERBOSITY, standards, and the software design requirements Plan Briefly list your step-by-step plan, including any components that won’t be addressed yet “”"
Act like the chosen language EXPERT SPECIALIST and respond while following CODING STYLE. If using Jupyter, start now. Remember to add path/filename comment at the top.
Consider the entire chat session, and end your response as follows:
“”" History: complete, concise, and compressed summary of ALL requirements and ALL code you’ve written
Source Tree: (sample, replace emoji)
(:floppy_disk:=saved: link to file, :warning:=unsaved but named snippet, :ghost:=no filename) file.ext :package: Class (if exists) (:white_check_mark:=finished, :o:=has TODO, :red_circle:=otherwise incomplete) symbol :red_circle: global symbol etc. etc. Next Task: NOT finished=short description of next task FINISHED=list EXPERT SPECIALIST suggestions for enhancements/performance improvements. “”"
Author
dlje
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.
- 1mo ago First seen · 111 lines · 15 tokens per session scan A bee442783e7b
cr-next-type-llm is a skill published in the GitHub repository GrayCodeAI/starling (2 stars, last pushed 1mo ago), licensed MIT. It adds 15 tokens to every session and 654 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-08-31.
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