panera_at_work_locations

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

With no annotations provided, the description carries the full transparency burden. It discloses that the tool returns the 'full national Panera at Work location list,' describes the dataset as 'small,' and specifies the fields each location carries (address, coordinates, contact, lead time, service cafe id, scheduled times). It stops short of mentioning pagination or error behavior, but for a simple read-only list endpoint the key behaviors are covered.

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?

Three dense sentences, all purposeful. The main action is front-loaded in the first sentence; the second sentence differentiates from a sibling; the third lists return fields and the no-parameter requirement. No wasted words or repetitive restating of the tool name.

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?

For a zero-parameter national location list with no output schema, the description fully explains what the agent gets and its shape. It names all included data fields, clarifies the scope ('small, national dataset'), and explicitly states that no parameters are needed. Nothing essential is missing.

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 input schema has zero parameters, so the baseline is 4. The description adds value by reinforcing the zero-parameter expectation with 'no query parameters are needed,' which prevents an agent from inventing filters. No further parameter semantics are necessary.

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 opens with a specific verb and resource: 'Get Panera Bread's Panera at Work workplace-delivery locations.' It also explicitly distinguishes this from 'ordinary cafe pickup/delivery covered by GET /panera/locations,' making the tool's unique scope clear. An agent can immediately tell this is a B2B workplace-delivery location list separate from sibling tools.

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 states precisely when to use this tool versus alternatives by naming the sibling endpoint (GET /panera/locations) and characterizing this as the separate B2B program. It also explicitly notes 'no query parameters are needed,' removing any doubt about invocation.

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