discover_agents

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

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions 'discovery with filtering' but doesn't describe what the tool returns (e.g., list of agents, metadata), whether it's paginated, rate-limited, or requires authentication. For a discovery tool with 5 parameters, this leaves significant behavioral gaps unaddressed.

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 a single, efficient phrase that front-loads the core purpose without unnecessary words. Every word earns its place: 'Machine-to-machine' specifies the context, 'agent discovery' states the action, and 'with filtering' adds the key constraint. No waste or redundancy is present.

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 tool's complexity (5 parameters, no output schema, no annotations), the description is insufficient. It doesn't explain what 'discovery' entails (e.g., returns agent profiles, availability), how results are structured, or any behavioral traits like rate limits. For a filtering tool with multiple options, more context is needed to guide effective use.

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?

The description adds minimal value beyond the input schema, which has 100% coverage with detailed parameter descriptions. The phrase 'with filtering' implies the parameters are for filtering purposes, but this is already evident from the schema. No additional context about parameter interactions, default behaviors, or semantic meaning is provided, meeting the baseline for high schema coverage.

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's purpose as 'Machine-to-machine agent discovery with filtering', which specifies the verb (discovery) and resource (agents) with a key constraint (filtering). It distinguishes from siblings like 'get_agent' (single agent retrieval) and 'search_agents' (likely broader search), though it doesn't explicitly name these alternatives. The purpose is specific but could be more differentiated.

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?

The description provides no guidance on when to use this tool versus alternatives like 'search_agents' or 'get_agent'. It mentions filtering but doesn't clarify if this is the primary discovery method or when other tools might be more appropriate. No context about prerequisites, exclusions, or typical use cases is provided.

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