Giornata Mondiale

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

Annotations already declare the tool read-only, idempotent, and non-destructive, so the description does not need to restate those traits. It adds useful behavioral context by specifying the exact data scope and the provenance of the required identifier, going beyond what annotations provide.

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 one sentence that front-loads the main purpose and includes only relevant details: what is fetched and where the identifier comes from. There is no filler, repetition, or unnecessary elaboration.

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?

With a single parameter, rich annotations, and an output schema present, the description covers everything needed to invoke the tool correctly. It explains what data the call returns and how to obtain a valid identifier, while the output schema handles return-value details.

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 coverage for the single 'id' parameter is 0%, so the description carries the burden of explaining it. It does this well by defining the parameter as an 'exact day identifier returned by search or list_days', which tells the agent where to obtain a valid value. It stops short of giving an explicit format or examples, but for a single parameter this 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 names a specific verb ('Fetch') and a precise resource: published editorial text, dates, primary sources, and correction history for an exact day identifier. It distinguishes itself from siblings by stating the identifier must come from search or list_days, so an agent can tell it apart without inspecting schemas.

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 clear guidance on when to use the tool: after obtaining an exact day identifier from search or list_days. It does not explicitly list exclusions, such as when to prefer list_topics or list_days, but the input-source constraint is enough to prevent obvious misuse.

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?

The description reveals several non-obvious behaviors beyond the read-only/idempotent annotations: the 366-day maximum, Europe/Rome default, resolution of movable annual dates, and exclusion of expired recurrences. These details meaningfully help an agent understand what will happen when invoking the tool.

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?

Three short sentences, each carrying distinct value: operation scope, default behavior, and recurrence handling. No redundant wording, and the most important information is front-loaded.

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 description covers core date semantics and recurrence behavior, while the output schema and annotations fill in return-shape and safety details. It is slightly short on explicit alternative-tool guidance and timezone interpretation for user-supplied dates, but it remains adequate for correct 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?

With 50% schema description coverage, the description compensates for date parameters by adding the inclusive-range cap and the timezone default. The schema already documents topic, start_date, end_date, authority_status, and limit/offset constraints, so the combination 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 uses a specific verb and resource: 'List days on a date or in an inclusive date range', with an explicit maximum range of 366 days. It is clear and unambiguous, but it does not explicitly contrast with sibling tools such as search, fetch, or list_topics, so it stops short of full sibling differentiation.

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 first sentence states the exact use case—listing days for a date or date range—and the default timezone clarifies behavior when dates are omitted. It does not explicitly list when-not-to-use or point to alternatives, but the context is clear enough for an agent to know when this tool applies.

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?

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so safety is well covered. The description adds the 'public' scope, which is useful, but does not disclose pagination behavior or any other runtime characteristics beyond what the schema's limit/offset parameters imply.

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?

Two sentences with no filler. The core purpose is stated first, and the usage hint is secondary but still valuable. Every 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?

For a simple paginated list tool with read-only annotations and an output schema, the description conveys the essential purpose and how results connect to sibling tools. It could mention pagination explicitly, but the limit/offset parameters and output schema cover most of what an agent needs.

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 needed to compensate for the limit and offset parameters. It does not mention them at all; it only describes the output. The parameter names and constraints are somewhat self-explanatory, but the description provides no additional meaning such as pagination semantics or result ordering.

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 ('List'), a clear resource ('public topics'), and the exact data returned ('names, slugs and record counts'). This distinguishes it from the sibling tools, which are about retrieval or listing days, not topic enumeration.

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 concrete guidance on how the output should be used ('Use a slug as the topic filter in search or list_days'), which tells the agent the purpose of the returned slugs. It does not explicitly exclude cases where this tool should not be used, but the context is clear enough for selection.

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?

Annotations already establish read-only, idempotent, non-destructive behavior. The description adds meaningful behavioral context by stating that results are citable and carry an explicit verification status, and that the tool returns search results rather than full details. No contradiction with annotations.

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?

Three short sentences that front-load the tool's purpose, summarize output characteristics, and close with clear routing guidance. Every sentence earns its place with no filler or repetition.

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 search tool with an output schema and safety annotations, the definition covers the search scope, key result characteristics, and the relationship to `fetch`. Pagination and `authority_status` semantics are left to schema defaults and enums, which is acceptable, though a brief note about `list_topics` for topic slugs would make it fully airtight.

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 only 20% schema description coverage, the description compensates by defining the `query` parameter as matching title, official title, description, or topic, and by mentioning verification status, which relates to `authority_status`. It does not explain `limit`/`offset` mechanics or all filtering semantics, but the schema provides defaults and enum values for those.

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 ('Search') on a defined resource ('Italian world and international days') and enumerates the searchable fields: title, official title, description, or topic. It also distinguishes itself from the sibling `fetch` by directing users there for details.

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?

Provides a clear routing instruction with 'Use fetch for details,' which clarifies when to use this tool versus the sibling. However, it does not explicitly discuss when to choose `list_days` or `list_topics` instead, so the guidance is clear but not exhaustive.

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