whycant

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

With no annotations provided, the description successfully discloses key behavioral traits: it is read-only, incurs no rate-limit cost, and returns shareable /result URLs. It does not fully detail pagination mechanics or whether full roast content is returned, but the most important safety and cost aspects are clear.

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 two sentences long, front-loaded with the core action (page through roasts) and immediately provides use case guidance. Every phrase adds value; no unnecessary words. Excellent conciseness.

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 simple parameters, no required fields, and no output schema, the description is mostly complete. It explains what the tool does, when to use it, and its read-only nature. Minor gap: no mention of pagination limits beyond the limit parameter, and no example of return fields. Still, adequately complete for the complexity level.

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?

Input schema has 100% coverage, providing descriptions for all three parameters. The description adds little beyond schema: it lists sort options (already in enum) and mentions query filters over name/problem (already in schema). No additional detail on limit or pagination behavior. Hence baseline 3 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 clearly states the tool pages through existing public roasts (the /explore feed) with shareable URLs. It specifies the resource (public roast corpus) and action (browse/page) and distinguishes itself from siblings like roast_idea by suggesting use case: see if idea was already roasted before minting a new one.

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 explicitly tells when to use this tool: to check if an idea was already roasted before creating a new one. It also mentions that it's read-only and has no rate-limit cost, encouraging use without risk. This contrasts with sibling tools like roast_idea (which creates) and provides strong guidance.

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. It discloses read-only behavior and no rate-limit cost, and lists the returned data. This adequately informs an agent about the tool's behavior, though it could mention error conditions or data freshness.

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 two sentences, front-loaded with the resource and data points, then adding behavioral traits. No redundant or ambiguous wording.

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 no output schema and no parameters, the description fully explains what the tool returns (specific stats) and its safety profile (read-only, no rate-limit cost). It is complete for the tool's simplicity.

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 tool has zero parameters, and the schema coverage is 100%. Baseline is 4, and the description adds no unnecessary parameter information, 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 specifies the exact resource (public stats from whycantwehaveanagentforthis.com) and lists the specific data points returned (total ideas roasted, live results, etc.). This clearly distinguishes it from siblings like browse_explore, get_verdict, and roast_idea.

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?

Explicitly states 'Read-only, no rate-limit cost,' guiding the agent that this tool is safe to call without side effects or resource concerns. While it doesn't explicitly list when not to use it, the simple stateless nature and distinct siblings provide clear context.

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 provided, but description compensates fully by declaring read-only, no new analysis, no rate-limit cost, and same return shape as roast_idea.

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, no wasted words. Front-loaded with purpose and usage, then behavioral note.

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?

Simple tool with one parameter, output schema exists. Description covers all necessary aspects without redundancy.

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 already describes parameter well (100% coverage). Description reinforces by mentioning 'id or slug' and linking to roast_idea, adding minimal extra value.

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?

Explicitly states fetching an existing verdict by id or slug. Distinguishes from sibling roast_idea by contrasting as read-only and noting same return shape.

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?

Clearly specifies what input to provide (result id or slug) and that it's read-only with no rate-limit cost, implying usage context. No explicit when-not-to-use, but adequate.

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, but the description discloses key behaviors: every call creates a persistent result page, rate limits (3/hour, 10/day anonymous), and optional token for higher limits. This fully informs the agent of the tool's side effects and constraints.

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 dense paragraph that front-loads the purpose. It is concise but could be slightly more structured (e.g., breaking out rate limits). Overall it is efficient.

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 simplicity (1 parameter, output schema exists), the description covers all necessary context: what the tool returns, behavioral traits, and rate limits. It is complete for an agent to use effectively.

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% for the single parameter 'idea', which already describes it well. The description adds an example but no additional semantics beyond the schema, so a baseline of 3 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 clearly states it provides a 'roast' for an AI agent idea, listing specific outputs (verdict tier, readiness score, etc.), and distinguishes from sibling tools like browse_explore, get_stats, and get_verdict which serve different purposes.

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 for roasting ideas but does not explicitly state when to use or not use this tool versus alternatives. Sibling tools are different enough, but no when-to-use guidance is provided.

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