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 itallstartedwithaidea/agent-skills --skill ai-chat-studiogit clone --depth 1 https://github.com/itallstartedwithaidea/agent-skillsWrote 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/itallstartedwithaidea/agent-skills/ai-chat-studio)<a href="https://agentmods.dev/skills/itallstartedwithaidea/agent-skills/ai-chat-studio"><img src="https://agentmods.dev/badge/skills/itallstartedwithaidea/agent-skills/ai-chat-studio/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/itallstartedwithaidea/agent-skills/ai-chat-studio"><img src="https://agentmods.dev/badge/skills/itallstartedwithaidea/agent-skills/ai-chat-studio.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 | $0.00033 | $0.01604 |
| Opus 5 | $0.00016 | $0.00802 |
| Sonnet 5 | $0.00007 | $0.00321 |
| Haiku 4.5 | $0.00003 | $0.00160 |
Grade A, and why
ai-chat-studio 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 — 167 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AI Chat Studio
Part of Agent Skills™ by googleadsagent.ai™
Description
AI Chat Studio provides a multi-LLM chat orchestration framework with 300+ assistant presets, intelligent model routing, and conversation management. The agent configures and manages interactions across multiple language model providers—OpenAI, Anthropic, Google, open-source models—selecting the optimal model for each task based on capability, cost, and latency requirements.
Not every task needs the most powerful model. A code review benefits from a reasoning-heavy model; a translation task runs well on a mid-tier model; a simple reformatting task wastes money on anything beyond a fast, cheap model. This skill implements intelligent routing that matches task characteristics to model capabilities, reducing cost by 40-60% while maintaining quality where it matters.
The 300+ assistant presets encode domain-specific system prompts, temperature settings, and output format constraints for common tasks: code generation, technical writing, data analysis, creative ideation, customer support, legal review, and more. Each preset is tested against a quality benchmark and tagged with the models it performs best on.
Use When
- Configuring multi-provider LLM access in an application
- Routing tasks to the optimal model by cost-quality trade-off
- Managing conversation history and context windows
- Deploying domain-specific AI assistants with curated presets
- Building chat interfaces with streaming responses
- Comparing model outputs for the same prompt across providers
How It Works
graph TD
A[User Message] --> B[Task Classifier]
B --> C{Task Type}
C -->|Complex Reasoning| D[Claude 4 / GPT-4o]
C -->|Code Generation| E[Claude 4 / Codestral]
C -->|Translation| F[GPT-4o-mini / Gemini Flash]
C -->|Simple Format| G[Haiku / Flash]
D --> H[Apply Preset: System Prompt + Params]
E --> H
F --> H
G --> H
H --> I[Manage Context Window]
I --> J[Stream Response]
J --> K[Log Usage + Cost]
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 · 167 lines · 33 tokens per session scan A 42f54365c932
ai-chat-studio is a skill published in the GitHub repository itallstartedwithaidea/agent-skills (37 stars, last pushed 4mo ago), licensed MIT. It adds 33 tokens to every session and 1,604 once invoked, about $0.0002 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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