> For the complete documentation index, see [llms.txt](https://docs.fastrouter.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.fastrouter.ai/integrations/agents.md).
# Agents
Agent workloads fan out into many LLM calls per run, so cost and reliability matter more here than anywhere else. Every framework below accepts an OpenAI-compatible client, which is all FastRouter needs. Point it at FastRouter and each agent call routes through one endpoint with:
* **100+ models** from OpenAI, Anthropic, Google, xAI, Meta, Groq, and Mistral behind one key. Assign a cheap model to triage agents and a frontier model to reasoning-heavy ones without juggling provider credentials.
* **Observability** on every request: cost, tokens, latency, and model per call, visible in your [dashboard](https://dashboard.fastrouter.ai/).
* **Reliability** through automatic failover across providers, response caching, and intelligent routing.
* **Governance** with per-key budgets, rate limits, model restrictions, role-based access, and project isolation.
The pattern is the same everywhere: create an OpenAI-compatible client with FastRouter's base URL, pass it a model slug in `provider/model-name` format.
---
# Agent Instructions
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## Querying This Documentation
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Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:
```
GET https://docs.fastrouter.ai/integrations/agents.md?ask=&goal=
```
`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
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