Quick Lotto lottery results

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

No annotations are present, so the description carries the full transparency burden. It usefully discloses aggregate scope (every lottery in one call), but is silent on return format, caching, or potential side effects. Read-only nature is implied but not stated.

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 minimal, high-signal wording. The first sentence states the result and scope; the second gives concrete usage examples. No redundancy or filler.

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-parameter read operation, the description covers the what and when-to-use adequately. It lacks an output schema but does state the returned concept ('winning numbers'). A more formal structure description would be nice, but is not essential for tool selection.

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 zero parameters, so parameter semantics are trivially satisfied. The description reinforces the no-input call with 'in one call' and adds no confusing detail. This matches the baseline for a 0-parameter tool.

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 identifies the exact object ('most recent winning numbers') and scope ('every lottery covered, in one call'). It also distinguishes from siblings by explicitly contrasting with questions that name a specific past date, making this tool's purpose 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?

Provides clear usage examples ('what were last night's numbers') and an exclusion criterion ('does not name a specific past date'). It does not explicitly name the alternative tool, but sibling 'lottery_results' is the obvious candidate for date-specific queries.

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 clearly indicates this is a listing operation (read-only implied) but does not disclose the output format, pagination, or whether the list could be empty. For a zero-parameter tool, it is adequate but lacks the richness that annotations would normally cover.

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 fluff. The first packs all essential output details, and the second gives a direct usage pointer. Information is front-loaded and 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 tool with no parameters and no output schema, the description covers what it returns, why it's useful, and when to call it. It is fully sufficient for an agent to decide to invoke it confidently.

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?

There are no parameters, so schema coverage is 100% and the baseline is 4. The description correctly avoids repeating the empty schema and adds no parameter-specific semantics, which is appropriate here.

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 identifies the resource (lotteries) and the specific details returned (draw machine size, official ticket lotteries). It distinguishes itself from siblings like latest_results and lottery_results by framing itself as the initial discovery tool with the explicit 'Call this first' instruction.

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 explicit guidance on when to use: 'Call this first if you are unsure which lotteries are covered or what code to use.' This is a clear trigger, but it does not explicitly spell out when to prefer the sibling tools, though it implies they are for when the user already knows the lottery.

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 transparency burden and does disclose the key behavioral distinction between recent-history mode and specific-date mode. It gives an accurate sense of what the operation returns, though it does not discuss output structure, error behavior, or edge cases. For a low-risk read-only tool, that is adequate but not detailed.

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 definition is two short sentences with no filler: the core purpose and modes are front-loaded, and the list_lotteries instruction earns its place. It is compact while still conveying the essential behavior.

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 two-parameter tool with no output schema, this description covers the essential invocation facts: what data is returned, the optional-date behavior, and where to find valid lottery codes. It does not describe the return format or explicitly differentiate from latest_results, but given the low complexity these are minor omissions.

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 both parameters with 100% coverage, so the baseline is 3. The description adds value by specifying that 'lottery' is a code sourced from list_lotteries and clarifying that omitting 'date' yields the most recent draw. This is genuinely useful guidance beyond the schema text.

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 the resource ('Winning numbers for one lottery') and the two retrieval modes, making the tool's purpose clear. It also references list_lotteries for code sourcing, which helps separate it from the listing sibling. It stops short of explicitly contrasting itself with latest_results, so it is not a full 5.

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 establishes clear context: use this when you need winning numbers for a single lottery, either as recent history or for a specific past date. The instruction to pull codes from list_lotteries guides preparation, but there is no explicit guidance on when to prefer latest_results instead. Usage conditions are implied rather than spelled out.

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