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

No annotations are provided, so the description carries the full burden for behavioral disclosure. The word 'safely' suggests a pure, side-effect-free operation, which is a useful trait. However, it does not disclose edge-case behavior like operator support, error handling, or precision limits. For a calculator tool, 'safely' plus 'basic arithmetic' gives a basic picture but leaves room for more detail, warranting a mid-score.

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 that states the purpose and gives an example. There is zero redundancy and every word contributes to understanding. The example is placed early, reinforcing the purpose immediately. This is an exemplar of concise, structured tool documentation.

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 has a single parameter and an output schema, so return format is covered. The description mentions 'basic arithmetic' and an example, which covers the core usage. However, it omits details like the set of supported operators, handling of division by zero, or error messages. For a simple calculator this might be adequate, but it leaves some gaps that an agent might need, especially since no annotations exist. A 3 reflects that it is functional but not thorough.

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 compensate. It provides one concrete example ('(25 * 4) + 10') which illustrates the expected string format and suggests operator usage (parentheses, multiplication, addition). This goes beyond the bare schema but does not fully specify syntax rules, allowed operators, or precedence behavior. The example is helpful but partial, making 3 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?

The description clearly states a specific verb ('calculate') and a well-defined resource ('basic arithmetic') with a concrete example. It unambiguously distinguishes itself from siblings like get_current_time and find_student, which serve entirely different purposes. An agent can instantly tell what this tool does without needing to open the schema.

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 gives a sense of scope ('basic arithmetic') but does not explicitly state when to use this tool versus alternatives or when not to use it. There is no mention of exclusions such as more complex math or non-arithmetic calculations. The example implies usage, but no explicit routing or conditions are provided. Siblings are unrelated, so the context is clear enough, but formal guidance is missing.

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 disclosing behavioral traits. It does not state whether the operation is read-only, whether it can return multiple matches, what happens if no student is found, or any potential side effects. While it implies a safe lookup, it fails to convey critical behavioral context such as error behavior or data scope limitations.

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, well-structured sentence that front-loads the action verb and places the key qualifier ('demo') early. Every word earns its place, providing essential information without any fluff or redundancy.

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 (one required parameter, no nested objects, output schema present). Given that an output schema exists, the description need not detail return formatting. It correctly identifies what the student data covers (course, attendance, enrollment status) and the lookup criterion. The only omission is explicit guidance on edge cases, but these are less critical for such a straightforward tool.

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?

With 0% schema description coverage, the description must clarify the parameter's meaning. It does so implicitly by stating 'by name', which aligns with the 'name' parameter. However, it does not elaborate on the expected format (e.g., full name vs partial, case sensitivity) or whether the name is case‑insensitive. The description adds only minimal value beyond the schema's bare string type.

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 (find), the target (demo student), the specific pieces of information returned (course, attendance, and enrollment status), and the lookup method (by name). It is instantly distinguishable from the unrelated sibling tools 'calculate' and 'get_current_time', so an agent can route correctly without opening the schema.

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 the tool should be used when a student's details are needed by name, but it provides no explicit guidance on when it is appropriate versus alternatives, nor any exclusions or prerequisites. The context is unambiguous but under-specified, leaving the agent to infer usage from the purpose alone.

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. It states a 'Get' operation, which implies a read, but does not explicitly mention non-destructiveness, error handling, or format. For a simple time function this is adequate, but it adds no behavioral detail beyond the obvious.

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?

A single, front-loaded sentence with zero fluff. Every word contributes to specifying the tool's function and the parameter's format. Perfectly sized for its purpose.

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, the presence of an output schema, and the clear sibling context, the description covers everything an agent needs to invoke it correctly. No missing critical information.

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 compensate. It adds the crucial constraint that timezone must be an IANA identifier and provides an example (Asia/Karachi), giving meaning beyond the bare schema property name. However, it doesn't elaborate on accepted formats or validation, so not a 5.

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 verb 'Get', the specific resource 'current date and time', and constrains it to 'an IANA timezone'. This unambiguously distinguishes it from siblings (calculate, find_student) without needing to open the schema.

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 is implied by the tool name and description, but no explicit statement about when to use it vs alternatives is given. There is no mention of exclusions or alternatives, though the sibling tools are clearly different in purpose.

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