afferens_perceive

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

No annotations are provided, so the description carries the full burden. It discloses the read-only nature (querying events) and mentions real-time updates, but does not cover rate limits, pagination, or error handling. Additional context like token usage for the free tier is helpful.

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?

Two sentences, front-loaded with the purpose, followed by essential usage context (API key, free tier). No superfluous words; every sentence adds value.

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?

With no output schema, the description outlines the return types (object detections, positions, etc.) but lacks structure details (e.g., field names). It covers key constraints (API key, token limit) and parameter options. A bit more on error handling or expected response format would improve completeness.

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?

Both parameters are fully described in the schema (coverage 100%). The description adds value by explaining what each modality returns (e.g., 'object detections, positions, sounds'), providing semantic context beyond the enum labels. However, it does not detail default behavior for omitted parameters.

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 action ('Query live physical perception events') and resource ('sensory layer'), listing specific data types returned. It distinguishes from sibling tools like 'afferens_actuate' by focusing on perception rather than action.

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 explains the API key requirement and free tier limitations, which is useful for setup. However, it does not explicitly guide when to use this tool versus siblings (e.g., when to use 'afferens_ingest' instead) or state when not to use it.

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