Zovo Raffle Tickets

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

Beyond the annotations (readOnlyHint=true, idempotentHint=false), the description explains the sampling semantics (without replacement, duplicate names count as multiple entries, exclusions applied before the draw) and the non-idempotency rationale, which the bare idempotentHint=false flag does not convey. It also discloses the artifacts produced (ordered winners, a draw log PDF and CSV containing time, method, entry count and an entry-list fingerprint), so an agent knows a fresh random result is generated on every call.

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?

It opens with the use-case triggers, then moves to mechanism, outputs, and limits — well front-loaded with no filler sentences. It is dense and somewhat long, but each clause carries distinct information; minor tightening of the output/log sentence would make it crisper.

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 9-parameter tool with an output schema, the description covers what an agent still needs: valid entry forms, draw semantics, the non-repeat-call warning, and scope boundaries (no sales, no legal advice). Return values are summarized rather than re-specified, correctly deferring to the output schema.

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 is 100%, so the baseline is 3, but the description adds real meaning: ranges are expanded, a name repeated three times yields three entries, the first winner takes the first prize, and exclusion is applied before the draw (void tickets, prior winners). It does not restate defaults for every parameter, relying on the schema for counts and alternates, which is 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 states a specific verb and resource — drawing raffle winners (plus optional alternates) without replacement using a secure RNG — and gives concrete entry forms (1-500 range, multiple sold ranges, name lists). It does not name the sibling generate_raffle_tickets or explicitly contrast drawing winners with generating tickets, so sibling differentiation is only implicit.

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?

It gives explicit trigger intents ('when the user wants to draw a raffle winner, pick random winners from ticket numbers or names, or use a raffle number generator with no repeats') plus a clear anti-pattern: 'Each call is a new draw, so do not call it again to change a result.' It also fences off adjacent-but-out-of-scope requests (selling tickets, payments, legal advice).

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?

Beyond the annotations, the description discloses the return artifact (print-ready PDF), layout behavior (10 or 8 tickets per US Letter or A4 sheet), numbering guarantees (sequential with no gaps or repeats), and a hard limit of 2,000 tickets per call. It also clarifies important exclusions around sales, payments, and legal compliance.

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 front-loaded with the usage condition, then moves to output details, limits, and exclusions in a compact three-sentence structure. Every sentence adds useful information without 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?

With 16 optional parameters and full schema coverage, the description provides sufficient context about the generated artifact, numbering behavior, sheet layout, capacity limit, and scope exclusions. Because an output schema exists, it need not explain return values in greater detail.

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 is 100%, so the schema already documents every parameter thoroughly. The description reinforces the overall constraint of up to 2,000 tickets and describes sheet layout, but adds little parameter-specific meaning beyond what is already in the schema.

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 and resource: generating printable raffle tickets, and describes the exact deliverable (a print-ready PDF with numbered tickets and stubs). It is easy to distinguish from the sibling draw_raffle_winners because this tool produces ticket sheets, not draw results.

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 opening sentence gives a clear when-to-use condition tied to user intent, and the final sentence states what the tool does not do (sell tickets, collect payments, check legality). It does not explicitly name draw_raffle_winners as the alternative, so it falls short of full when/when-not/alternatives guidance.

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