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

No annotations are provided, so the description carries full burden. It only says 'Add two numbers together,' but does not disclose behavioral traits such as result type, precision, overflow handling, or error behavior. For a simple arithmetic tool, this may be passable, but it lacks depth.

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, coherent sentence with no extraneous words. It efficiently conveys the tool's purpose. Front-loading is not an issue due to its brevity.

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 simplicity (2 numbers, arithmetic operation), the description is adequate but incomplete. It does not mention the return value (output schema exists but is not described), nor does it address edge cases, making it insufficient for complex usage.

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 description coverage is 0%, meaning parameters have no descriptions. The description adds no semantic context beyond the schema (that a and b are numbers). It does not explain what the numbers represent, range constraints, or units, leaving the agent with minimal guidance.

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 action (add) and the object (two numbers), and it distinguishes from sibling arithmetic tools like subtract, multiply, etc. It is specific and unambiguous.

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 implies usage when addition is needed, but provides no explicit guidance on when to use this tool versus alternatives, nor any context about prerequisites or restrictions. The sibling tools differentiate by operation, but the description does not elaborate.

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 exist, so the description must fully disclose behavioral traits. It only states the division operation and says nothing about edge cases like division by zero, error handling, or return type behavior. For a pure computation tool, this is a significant gap.

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, front-loaded sentence with no wasted words. It conveys the essential operation and operand order compactly, making it efficient for an agent to parse.

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?

Despite the simple nature of the tool, the description omits key behavioral context such as division-by-zero behavior. An output schema exists but likely only describes the return type, not error cases. The description is too sparse to be considered complete for safe invocation.

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 description coverage is 0%, so the description adds the crucial semantic that 'a' is the dividend and 'b' is the divisor. However, it does not provide additional constraints or expectations (e.g., non-zero denominator), leaving the agent to assume the schema's minimal information is sufficient.

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 'Divide a by b' clearly states the operation and the roles of the two operands, distinguishing it from add, subtract, and multiply. It is not a mere tautology of the tool name because it specifies the argument order, making the intent unambiguous.

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?

There is no guidance about when to use this tool versus the sibling arithmetic tools or any exclusions. While the operation is self-evident, the description does not explicitly state conditions or alternatives, leaving the agent to infer usage.

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?

For a pure arithmetic operation, 'Multiply a and b' transparently conveys behavior: no side effects, no mutation, no hidden state. With no annotations provided, the description is adequate, though it does not discuss edge cases like overflow or type coercion.

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 sentence with zero filler, and the core operation is front-loaded. This is appropriately sized for a two-parameter pure 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?

The tool is simple, the input schema fully specifies both required numeric parameters, and an output schema is present. Nothing essential is missing for an agent to call this tool correctly.

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 description coverage is 0%, so the description must clarify parameter roles. It identifies a and b as the multiplicands, but adds no further semantic detail beyond what the schema's number type and requiredness already provide.

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 states the exact operation ('Multiply') on the named operands a and b, which fully specifies the tool's function. It is clearly distinct from its arithmetic siblings add, subtract, and divide.

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?

Usage must be inferred from the operation itself: an agent needing a product would select this tool. However, no explicit guidance or alternatives are named, and there are no statements about when not to use this tool.

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, the description carries the full burden of explaining behavior. It clearly specifies the order of operands (b from a) but does not disclose additional traits such as return type, edge cases, or side effects. For a simple arithmetic function, this is minimal but adequate; however, it lacks richness beyond the core operation.

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, focused sentence with no filler words. It communicates the essential operation clearly and efficiently, earning a perfect score for conciseness.

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 simplicity of the tool, the explicit input schema, and the presence of an output schema (as indicated by context), the description provides sufficient context. It does not need to explain return values or complex behaviors, making it complete for its purpose.

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?

Although the input schema has no descriptions for a and b, the description adds critical semantic meaning by clarifying the subtractive relationship: a is the minuend and b is the subtrahend. This compensates for the 0% schema description coverage and helps the agent understand how to correctly pass arguments.

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 action as 'Subtract b from a', using a specific verb and resource. This unambiguously identifies the operation and distinguishes it from sibling tools like add, multiply, and divide.

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 implies use for subtraction but does not explicitly state when to choose this tool over alternatives. There is no mention of exclusions or competing tools, leaving the usage context to be inferred from the operation name and sibling context.

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