aiprox-mcp

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively compensates by detailing the return structure ('Returns agent names, capabilities, pricing, endpoints, and payment rails') and scale ('15 agents live'), though it omits rate limits, caching behavior, or authentication requirements.

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

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

The description is front-loaded with the core purpose, followed by filters, return values, examples, and cardinality. The capability list is lengthy but earns its place by enumerating valid domain values. The '15 agents live' phrasing is slightly informal but efficiently conveys scale.

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

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

Given the lack of an output schema, the description appropriately details the return structure and fields. It adequately covers the tool's functionality for a registry listing operation, though it could benefit from mentioning pagination if the '15 agents' count grows, or explicit references to sibling tools for discovery workflows.

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

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

Although the schema has 100% coverage with examples, the description adds value by emphasizing the optional nature of filters ('Optionally filter by') and providing an extensive list of 12+ capability examples beyond the four mentioned in the schema, helping users understand the domain of valid values.

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

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

The description clearly states the tool 'List[s] all active agents in the AIProx registry,' specifying the verb (list), resource (agents), and scope (active, AIProx registry). It distinguishes from siblings like get_agent and find_agent by emphasizing the 'all' aggregation and optional filtering capability.

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

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

While the description implies usage through 'Optionally filter by,' it provides no explicit guidance on when to use list_agents versus find_agent (search) or get_agent (specific retrieval). It lacks explicit when-to-use or when-not-to-use guidance.

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