uber_eats_track_orders

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'direct API' and 'fast results' which hints at behavior but doesn't explain error modes, authentication requirements, or what happens with delivered/cancelled orders. For a 0-parameter tool, there's minimal risk surface, which slightly mitigates the gap, but behavior is still underspecified.

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, compact and front-loaded with the core purpose first. 'Uses direct API for fast results' is slightly vague filler but not harmful. No waste, though the second sentence adds marginal 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?

The tool is simple (0 params, output schema present), so the description covers the essentials. However, the existence of the sibling uber_eats_track_active_orders creates genuine ambiguity about scope that the description doesn't resolve. 'Active and past orders' partially addresses this but could explicitly mention the sibling distinction.

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 tool has 0 parameters, so there is nothing to explain beyond the schema. The rubric gives a baseline of 4 for 0-param tools, and the description adds value by describing what output the user gets (status, restaurant, items, totals). The presence of an output schema covering return values also helps.

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 tracks 'active and past orders' and lists the data shown (status, restaurant, items, totals). The verb 'track' plus a specific resource is clear. However, it doesn't explicitly distinguish from the sibling 'uber_eats_track_active_orders', though the 'active AND past' phrasing implies broader coverage.

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 says 'uses direct API for fast results' but provides no guidance on when to use this vs the sibling uber_eats_track_active_orders. No exclusions, prerequisites, or alternative tool references are given. Given the ambiguity with a nearly identically-named sibling, this is a notable gap.

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