afferens_ingest

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

With no annotations, the description bears the full burden of behavioral disclosure. It reveals that an API key is required and that data becomes queryable via afferens_perceive. However, it does not disclose potential side effects, error behavior, idempotency, or any constraints beyond the key requirement.

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 remarkably concise: four sentences, each serving a distinct purpose. The first sentence states the primary action, the second gives usage context, the third explains downstream availability, and the fourth notes a prerequisite. No wasted words.

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 absence of an output schema, the description appropriately explains that ingested data becomes queryable via afferens_perceive, which addresses the post-condition. However, it lacks guidance on the data parameter's expected structure beyond the schema's brief note, and it does not mention the response format or error cases.

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?

All three parameters are described in the input schema with adequate detail (100% coverage). The tool description adds no additional semantic information about the parameters beyond what the schema already provides, earning a baseline score of 3.

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 action ('Push live sensor data into the Afferens sensory layer') and specifies the resource ('Afferens sensory layer'). It distinguishes from siblings by focusing on ingesting real-time perception events, while siblings like afferens_perceive are for querying and afferens_actuate for acting.

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 explicitly states when to use this tool: 'when your AI agent is connected to physical hardware and wants to contribute real-time perception events.' It does not explicitly mention when not to use it or provide alternative tools, but the context of contributing data versus querying (afferens_perceive) is implied.

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