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

With no annotations, the description carries the burden of behavioral disclosure. It clearly indicates a read-only retrieval of the current date and reveals the output format via the example. For a simple, side-effect-free getter, this is adequate even without explicit read-only phrasing.

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 sentence with no filler, front-loading the core behavior and including a precise example. Every word earns its place.

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?

This is a very simple tool with no required parameters, one well-documented optional parameter, and a clear output example. The description plus schema fully cover what an agent needs to call it correctly and interpret the result.

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 already documents the only parameter with full coverage, so the description does not need to explain it. The example '2025-03-15' adds some output-format context beyond the schema but not parameter-specific semantics. Baseline of 3 is appropriate given 100% schema coverage.

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 a specific verb ('Get'), a clear resource ('current date'), and a scope qualifier ('only') that distinguishes it from sibling tools get_time and get_datetime. The example format makes the tool's output 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 qualifier 'date only' clearly signals when to use this tool rather than get_time or get_datetime. However, it does not explicitly state exclusions like 'use get_datetime when both date and time are needed,' though the sibling names and the word 'only' make this reasonably inferable.

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 must carry the burden. It conveys a read-only intent with 'Get' and hints at return format through the example, but it does not clarify timezone behavior, formatting guarantees, or the absence of side effects beyond what is inferable.

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 sentence with a concrete example; no filler. The core behavior is front-loaded and the example grounds the expected output.

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 zero-required-parameter tool, the description plus schema and sibling context cover the essential call contract. It only lacks explicit guidance on choosing among get_datetime/get_date/get_time and a more formal output contract, but the example compensates.

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 100%; the only parameter, timezone, is already documented with allowed values and default. The description adds no extra meaning beyond the example, so it meets the baseline but does not exceed it.

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?

States a specific action and resource: 'Get the current date and time', with an example output. It is clear but does not explicitly contrast itself with sibling tools get_date and get_time, so it misses the strongest differentiation credit.

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 no guidance on when to choose this tool over get_date or get_time, and no exclusions or prerequisites. The intended use is only implied by the phrase 'current date and time'.

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 burden; it discloses the output scope ('time only') and format (HH:MM:SS) with an example. For a side-effect-free read operation this is sufficient behavioral transparency, though it leaves timezone default behavior to the schema description.

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 sentence with no filler; the verb, scope, and output example are front-loaded and every word adds 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 single-optional-parameter read tool, the description plus the schema fully covers the call: what it returns, the output format, and timezone options. It doesn't explicitly mention the default timezone in prose, but the schema already states it.

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 100% and the only parameter already documents allowed values ('local', 'utc', IANA string) plus default. The tool description adds no extra parameter semantics, so baseline 3 applies.

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 uses a precise verb-resource pair ('get current time') and narrows scope with 'only' plus a concrete example format ('14:30:00'), which clearly separates it from sibling tools get_date and get_datetime.

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 word 'only' signals that this tool is for the time component rather than date or full date-time, so usage context is clear. It does not explicitly name the sibling alternatives, but the intended selection is easy to infer from naming.

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