onthisday

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 it returns a list but doesn't describe format, pagination, rate limits, authentication needs, or error conditions. For a read operation with zero annotation coverage, this leaves significant gaps.

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's front-loaded with the core purpose and appropriately sized for a simple lookup tool.

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 read tool with two well-documented parameters and no output schema, the description is adequate but incomplete. It lacks behavioral details (e.g., response format, error handling) that would help an agent use it correctly, especially given the absence of annotations.

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 description adds minimal value beyond the input schema, which has 100% coverage. It mentions 'specific month and day' but doesn't explain parameter interactions or constraints beyond what the schema already documents (e.g., month 1-12, day 1-31). Baseline 3 is appropriate when the schema does most of the work.

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 specific action ('Get a list'), resource ('notable people born'), and scope ('on a specific month and day across all years'). It distinguishes from sibling tools like 'get_deaths' and 'get_events' by focusing exclusively on births rather than deaths or events.

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 sibling tools, prerequisites, or any contextual constraints. The agent must infer usage from the tool name 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 of behavioral disclosure. It describes a read operation ('Get a list'), implying it is non-destructive, but does not address other behavioral traits such as rate limits, authentication needs, error handling, or response format. For a tool with zero annotation coverage, this leaves significant gaps in understanding how it behaves.

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 efficiently conveys the tool's purpose without unnecessary words. It is front-loaded with the core action and includes essential details like scope ('across all years'), making it easy to parse. Every part of the sentence 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?

Given the lack of annotations and output schema, the description is incomplete for effective tool use. It does not explain what the return value includes (e.g., list structure, fields like names or years), potential limitations (e.g., data source, pagination), or error conditions. For a tool with no structured output information, the description should provide more context to compensate.

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 clear documentation for both parameters ('month' and 'day'), including their types and valid ranges. The description adds no additional parameter semantics beyond what the schema provides, such as format details or usage examples. According to the rules, with high schema coverage (>80%), the baseline score is 3.

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: 'Get a list of notable people who died on a specific month and day across all years.' It specifies the verb ('Get'), resource ('list of notable people'), and scope ('across all years'), making it easy to understand. However, it does not explicitly differentiate from sibling tools like 'get_births' or 'get_events' beyond the focus on deaths, which is implied but not stated.

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 does not mention sibling tools like 'get_births' or 'get_events' for comparison, nor does it specify any prerequisites, exclusions, or contextual cues for usage. The agent must infer usage based on 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It describes a read-only operation ('Get a list'), but lacks details on permissions, rate limits, pagination, or response format. The absence of annotations means critical behavioral traits are undocumented, leaving gaps for an AI agent.

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 front-loads the purpose without unnecessary words. It directly conveys the tool's function and scope, making it easy to parse and understand 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 low complexity (2 simple parameters, no output schema, no annotations), the description is adequate but incomplete. It covers the basic purpose and parameters but lacks behavioral details (e.g., response structure, error handling), which are needed for full contextual understanding in the absence of annotations.

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, fully documenting both parameters (month and day) with their types and ranges. The description adds no additional parameter semantics beyond what the schema provides, such as format examples or edge cases, so it meets the baseline for high 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 clearly states the verb ('Get') and resource ('list of historical events'), specifying the scope ('on a specific month and day across all years'). It distinguishes from siblings by focusing on general events rather than births or deaths, though it doesn't explicitly name the alternatives.

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 context by specifying 'historical events on a specific month and day,' suggesting it's for date-based queries. However, it doesn't provide explicit guidance on when to use this versus the sibling tools (get_births, get_deaths), nor does it mention any prerequisites or exclusions.

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