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

With no annotations provided, the description carries the full burden of behavioral disclosure. It reveals that the tool is metered (1 token per row), implying cost and pagination. However, it does not disclose authorization requirements, error handling, side effects, or whether the call is read-only. The cost hint is helpful but incomplete.

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 extremely concise: three short sentences deliver purpose, cost warning, and key parameter guidance. Every phrase earns its place with no redundancy or fluff. It is front-loaded with the core function.

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 tool has 7 parameters, no output schema, and no annotations, the description covers the basics but lacks depth. It mentions location inputs and limit, but does not explain the type parameter reliance on get_catalog, the travel time modes, or the response format. For a tool of moderate complexity, it is adequate but not comprehensive.

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 coverage is only 57% (4 of 7 parameters have descriptions). The description adds critical meaning by clarifying the mutual exclusivity of block_geoid vs lat+lon, which is not evident from the schema. It also reinforces the purpose of limit to control spend. However, it does not elaborate on mode, type, or max_minutes beyond the schema.

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 tool returns nearby points of interest with travel times from a location. It identifies the key resources (POIs and travel time) and hints at the use of coordinates or block_geoid. However, it does not explicitly differentiate from sibling tools like isochrone or blocks_in_area, which may also deal with geographic data.

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 advises to 'Give block_geoid or lat+lon' and to 'Keep limit small to control spend and context size', which provides some usage context. However, it does not specify when to prefer this tool over alternatives like find_place or isochrone, nor does it mention prerequisite calls like get_catalog for type ids.

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

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

No annotations provided, so description carries full burden. It discloses the side effect (emailing a code), the required user action, and the next step. It also mentions the ultimate goal (get API key with free tokens). Minor omission: no mention of error cases or duplicate emails.

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 with no wasted words. Front-loaded with action and purpose. Every sentence adds 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?

Given low complexity (1 parameter, no output schema), description is complete: it explains the tool's role, the required user input, and the subsequent step. No 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?

Input schema covers 100% of parameters with description 'The user's email address.' Description adds no further semantics beyond the schema, so baseline 3 is appropriate.

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?

Description clearly states the tool's purpose: 'Start free sign-up for the user: email them a six-digit code.' It specifies the verb ('start'), resource ('sign-up'), and mechanism ('email code'), distinguishing it from sibling tools like redeem_code which is the next step.

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?

Explicit usage guidance: 'The user must read the code from their own inbox and give it to you, then call redeem_code.' This tells when to use (first step of sign-up) and what follows, differentiating from siblings.

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