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route_request

Route AI requests to the optimal model by evaluating task, cost, speed, and compliance requirements. Selects the best model for each request.

Instructions

Route an AI request to the optimal model based on task, cost, speed, and compliance requirements.

Behavior: This tool is read-only and stateless — it produces analysis output without modifying any external systems, databases, or files. Safe to call repeatedly with identical inputs (idempotent). Free tier: 10/day rate limit. Pro tier: unlimited. No authentication required for basic usage.

When to use: Use this tool when you need structured analysis or classification of inputs against established frameworks or standards.

When NOT to use: Not suitable for real-time production decision-making without human review of results.

Args: task (str): The task to analyze or process. priority (str): The priority to analyze or process. max_cost (float): The max cost to analyze or process. require_compliance (str): The require compliance to analyze or process. prefer_local (bool): The prefer local to analyze or process. api_key (str): The api key to analyze or process.

Behavioral Transparency: - Side Effects: This tool is read-only and produces no side effects. It does not modify any external state, databases, or files. All output is computed in-memory and returned directly to the caller. - Authentication: No authentication required for basic usage. Pro/Enterprise tiers require a valid MEOK API key passed via the MEOK_API_KEY environment variable. - Rate Limits: Free tier: 10 calls/day. Pro tier: unlimited. Rate limit headers are included in responses (X-RateLimit-Remaining, X-RateLimit-Reset). - Error Handling: Returns structured error objects with 'error' key on failure. Never raises unhandled exceptions. Invalid inputs return descriptive validation errors. - Idempotency: Fully idempotent — calling with the same inputs always produces the same output. Safe to retry on timeout or transient failure. - Data Privacy: No input data is stored, logged, or transmitted to external services. All processing happens locally within the MCP server process.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
taskYes
api_keyNo
max_costNo
priorityNobalanced
prefer_localNo
require_complianceNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Despite no annotations, the description includes a comprehensive 'Behavioral Transparency' section detailing side effects (none), authentication needs, rate limits, error handling, idempotency, and data privacy. This fully compensates for the lack of annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with clear sections and front-loaded purpose. However, the 'Args' section is somewhat wordy and could be more concise. Overall, every section adds value and the structure aids readability.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (6 parameters, 1 required, no enums, output schema exists), the description covers all key aspects: purpose, usage, behavioral traits, and parameter meanings. It also includes error handling and privacy details, making it highly complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The 'Args' section provides a one-line description for each parameter, but these descriptions are generic and repetitive (e.g., 'The task to analyze or process.'). They do not explain valid values, constraints, or how parameters affect routing. With 0% schema coverage, more detailed semantics would be beneficial.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The title and description clearly state the tool's purpose: routing AI requests to optimal models based on task, cost, speed, and compliance. This distinguishes it from sibling tools like cost_estimator, get_gateway_stats, and list_models.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit sections for 'When to use' and 'When NOT to use', offering clear guidance on appropriate contexts and limitations, such as not suitable for real-time production without human review.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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