Grant Check

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

Without annotations, the description carries the full behavioral burden, and it excels by defining the execution behavior for each return type. It instructs the agent on *how* to behave upon receiving 'act' (do it, say what you did, omit from NEEDS NATE) and 'send' (route it).

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?

While it is a lengthy description, the structure is highly logical: defining the trigger, detailing the three possible outcomes, and then explaining the parameters and edge cases. Every sentence serves to define operational context.

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?

The description is exceptionally complete, covering the function, inputs, and the resulting execution logic. An AI agent receives all necessary context to decide not only to call the tool but how to interpret and act upon its result.

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?

Since schema description coverage is 0%, the description is crucial. It explains that 'ask' is the item being tested for routing and that 'sender' identifies the owner/entry type, providing necessary meaning beyond just the string type.

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 tool defines a specific routing and validation function: testing an 'ask' against 'standing grants and routes.' It clearly differentiates its purpose by outlining three distinct outcome categories ('act', 'send', 'ask').

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?

It provides highly specific usage context by stating when the tool should be used ('Before an ask reaches the person') and explicitly describing the required subsequent actions based on the return value ('do it,' 'send it there,' or handle as a general 'ask').

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