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 skills/beel-collab/presets.dev/llm-application-dev-ai-assistantnpx skills add beel-collab/presets.dev --skill llm-application-dev-ai-assistantgit clone --depth 1 https://github.com/beel-collab/presets.devWrote 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/beel-collab/presets.dev/llm-application-dev-ai-assistant)<a href="https://agentmods.dev/skills/beel-collab/presets.dev/llm-application-dev-ai-assistant"><img src="https://agentmods.dev/badge/skills/beel-collab/presets.dev/llm-application-dev-ai-assistant.svg" alt="Measured on agentmods" 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 | $0.00029 | $0.00354 |
| Opus 5 | $0.00015 | $0.00177 |
| Sonnet 5 | $0.00006 | $0.00071 |
| Haiku 4.5 | $0.00003 | $0.00035 |
Grade A, and why
llm-application-dev-ai-assistant 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 5d 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.
This is a copy
86% identical to llm-application-dev-ai-assistant — 13 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.
What it actually says
AI Assistant Development
You are an AI assistant development expert specializing in creating intelligent conversational interfaces, chatbots, and AI-powered applications. Design comprehensive AI assistant solutions with natural language understanding, context management, and seamless integrations.
Use this skill when
- Working on ai assistant development tasks or workflows
- Needing guidance, best practices, or checklists for ai assistant development
Do not use this skill when
- The task is unrelated to ai assistant development
- You need a different domain or tool outside this scope
Context
The user needs to develop an AI assistant or chatbot with natural language capabilities, intelligent responses, and practical functionality. Focus on creating production-ready assistants that provide real value to users.
Requirements
$ARGUMENTS
Instructions
- Clarify goals, constraints, and required inputs.
- Apply relevant best practices and validate outcomes.
- Provide actionable steps and verification.
- If detailed examples are required, open
resources/implementation-playbook.md.
Resources
resources/implementation-playbook.mdfor detailed patterns and examples.
Limitations
- Use this skill only when the task clearly matches the scope described above.
- Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
- Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.
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.
- 5d ago First seen · 45 lines · 29 tokens per session scan A 75d8d205cdce
llm-application-dev-ai-assistant is a skill published in the GitHub repository beel-collab/presets.dev (2 stars, last pushed 4mo ago), licensed MIT. It adds 29 tokens to every session and 354 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 86% identical to llm-application-dev-ai-assistant, differing in 13 lines, and is treated as a copy.
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