ai_agent

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

No annotations are provided, so the description must carry full burden. It mentions a cost of 30 sats per call but fails to disclose other traits like idempotency, authentication requirements, or the significance of preimage and macaroon parameters. The description is too brief for a complex tool.

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 short and front-loaded, but it omits critical behavioral and parameter details, making it less effective. Every sentence should earn its place, but here one sentence is insufficient.

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 4 parameters, no output schema, and no annotations, the description is notably incomplete. It lacks guidance on usage scenarios, parameter behavior, and return values, leaving the agent with significant gaps.

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?

Schema description coverage is 50% (only preimage and macaroon have descriptions). The description adds no additional meaning beyond the schema; it does not explain 'task' or 'context'. With moderate coverage and no compensatory detail, the value is low.

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 it is a 'General-purpose AI agent' that 'handles any text task', which is a specific verb-resource combination. Among sibling tools like ai_classify, ai_summarize, etc., it stands out as the general option, providing clear distinction.

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 implies it should be used for any text task but does not explicitly state when to use it versus specialized siblings. No exclusions or alternatives are mentioned, leaving the agent to infer usage context.

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