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 states the tool performs calculations but lacks details on error handling (e.g., division by zero), performance limits, or output format. This is a significant gap for a tool with no structured safety or behavioral hints.

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 a single, efficient sentence with zero wasted words. It is appropriately sized and front-loaded, directly stating the tool's purpose without unnecessary elaboration, making it easy for an agent to parse quickly.

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's complexity (basic math with 3 parameters) and lack of annotations and output schema, the description is incomplete. It doesn't explain return values, error cases, or behavioral traits, leaving gaps that could hinder correct tool invocation by an AI agent.

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 100% description coverage, clearly documenting all three parameters (operation, a, b) with enums and types. The description adds no additional meaning beyond the schema, such as explaining parameter interactions or constraints, so it meets the baseline for high schema coverage without enhancing parameter understanding.

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 'Perform basic mathematical calculations' clearly states the tool's function with a specific verb ('perform') and resource ('calculations'), distinguishing it from sibling tools like 'echo' and 'uppercase'. However, it doesn't specify the exact operations or differentiate between types of calculations beyond 'basic', which prevents a perfect score.

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 provides no guidance on when to use this tool versus alternatives. It doesn't mention any context, prerequisites, or exclusions, such as handling complex math or other tools. This leaves the agent without direction on appropriate usage scenarios.

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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool echoes input but doesn't cover aspects like whether it's read-only, if it has side effects, error handling, or output format. For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

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 and front-loaded, consisting of a single sentence that directly states the tool's purpose without any wasted words. It efficiently communicates the core functionality in a minimal format.

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's low complexity (single parameter, no output schema, no annotations), the description is adequate but has clear gaps. It covers the basic purpose but lacks usage guidelines and behavioral details, making it minimally viable but not fully informative for an agent to use effectively in varied contexts.

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 schema description coverage is 100%, with the parameter 'message' fully documented in the schema. The description adds no additional meaning beyond the schema's details, such as examples or constraints. According to guidelines, this warrants a baseline score of 3 when the schema does the heavy lifting.

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's function ('Echo back the input text'), specifying both the verb ('echo back') and the resource ('input text'). However, it doesn't explicitly differentiate from sibling tools like 'calculate' or 'uppercase', which would require mentioning it returns the input unchanged versus performing transformations.

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 provides no guidance on when to use this tool versus alternatives. It doesn't mention scenarios where echoing is appropriate (e.g., testing, debugging) or contrast it with siblings like 'uppercase' for text modification or 'calculate' for computations, leaving usage context implied at best.

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 are provided, so the description carries the full burden of behavioral disclosure. It states the tool 'Convert[s] text to uppercase', which implies a transformation but doesn't cover aspects like error handling (e.g., for non-string inputs), performance characteristics, or side effects. For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

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 a single, efficient sentence that directly states the tool's function without any unnecessary words. It is front-loaded and wastes no space, making it easy for an agent to parse quickly. Every part of the sentence earns its place by conveying essential information.

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 simple transformation tool with one parameter and no output schema, the description is minimally adequate. It covers the basic purpose but lacks details on output format, error conditions, or behavioral nuances. Without annotations or an output schema, the agent might need to infer or test these aspects, leaving some gaps in completeness.

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 100% description coverage, with the parameter 'text' fully documented as 'The text to convert to uppercase'. The description adds no additional meaning beyond what the schema provides, such as examples or edge cases. Given the high schema coverage, a baseline score of 3 is appropriate as the schema does the heavy lifting.

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's purpose with a specific verb ('Convert') and resource ('text'), making it immediately understandable. It doesn't explicitly distinguish from sibling tools like 'calculate' or 'echo', but the function is distinct enough that confusion is unlikely. The description avoids tautology by not just restating the name 'uppercase'.

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 provides no guidance on when to use this tool versus alternatives like 'calculate' or 'echo'. It doesn't mention any specific contexts, prerequisites, or exclusions for usage. The agent must infer usage based solely on the tool's name and description without explicit direction.

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