whycant

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

With no annotations, the description carries the burden. It discloses read-only behavior, no rate-limit cost, and that results include shareable /result URLs. It stops short of detailing pagination mechanics (e.g., how to request the next page), but the term 'page through' and limit parameter imply standard pagination.

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, front-loaded with the core action, then a compact list of options and a use case. Every clause earns its place without redundancy or fluff.

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 tool is simple (3 optional params, no output schema) and the description covers the main behavior (browsing roasts), the data returned (result URLs), safety (read-only, no cost), and a concrete use case. It doesn't detail output format, but for a lightweight paginated list tool this is adequate.

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%, and the schema already provides descriptions for sort (with enum and default), limit (with max/default), and query ('Free-text filter over name/problem'). The description adds little beyond repeating the enum values and the query's purpose, so it stays at 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 opens with a specific verb ('Page through') and resource ('existing public roasts'), clearly identifying the /explore feed. It distinguishes from siblings by framing it as a read-only browsing tool used to check for prior roasts before creating 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?

Explicitly states a primary use case: 'use it to see whether an idea was already roasted before minting a new one.' It also notes read-only and no rate-limit cost, implying safe usage. However, it doesn't explicitly contrast with sibling tools like roast_idea, but the intent is clear.

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 burden of disclosing behavior. It states 'Read-only' (no side effects) and 'no rate-limit cost' (performance implication), along with 'Live' indicating real-time data. This covers the key traits for a simple stats tool, though it doesn't describe response format or potential latency.

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 pack all essential info: the resource, the specific data points, and behavioral caveats. No filler or redundancy; every phrase 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?

The description fully covers what the tool does and returns (list of stats), and with zero params and no output schema, there is no missing behavioral or usage information. An agent can confidently invoke this tool knowing exactly what it will get.

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 zero parameters, so the baseline is 4. The description adds no parameter details but none are needed. The schema coverage is trivially 100%, and the lack of parameters means no semantics to explain.

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 this tool provides 'Live public numbers' for a specific domain, listing the exact metrics (ideas roasted, live results, percentages, roast battles, MCP roasts). This distinguishes it from the sibling tools (browse_explore, get_verdict, roast_idea), 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 makes it obvious this is the go-to tool for aggregate stats, not for individual items or actions. It mentions 'Read-only, no rate-limit cost,' implying safe use anywhere, but it does not explicitly state when not to use it or name alternatives. Clear context without exclusions.

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 explicitly discloses read-only behavior, no new analysis, no rate-limit cost, and the output shape matching roast_idea. This covers key behavioral aspects, though error handling or not-found behavior is not mentioned.

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 concise sentences front-load the action and key constraints. There is no redundant or filler content; 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 one-parameter retrieval with an output schema, the description comprehensively covers purpose, read-only nature, cost implications, and output shape. It is complete for the tool's complexity.

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%, so the baseline is 3. The description's 'by result id or slug' adds no new meaning beyond the schema's detailed parameter description. It does not clarify formats or valid values further.

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?

Description clearly states the tool fetches an existing verdict by result id or slug, using a specific verb and resource. It distinguishes from sibling tools like roast_idea (which likely creates) and browse_explore/get_stats (which likely serve other 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 provides clear context for when to use this tool: to retrieve an already minted verdict, with emphasis on being read-only and without rate-limit cost. It does not explicitly name alternative tools, but the context strongly implies it. No explicit exclusions are given.

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 explicitly discloses that every call mints a real, persistent result page with an OG share card, meaning roasting also publishes the idea publicly from the IDE. It also discloses rate limits (anonymous: 3/hour, 10/day; token raises limits). This is strong behavioral disclosure beyond typical descriptions.

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 three sentences with no filler. It front-loads the main output, then the critical side effect, then rate limits. 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?

The description is complete for the tool's complexity: it covers the side effect of publishing, rate limits, and authentication note (anonymous vs token). Since an output schema is present, return values don't need to be spelled out. The only minor gap is absence of explicit privacy details, but 'mints a real, persistent result page' clearly implies public visibility.

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 already provides 100% coverage with a description and example for the single 'idea' parameter. The tool description does not add parameter-specific semantics, but it doesn't need to; the schema does the heavy lifting. 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 'Get the full whycantwehaveanagentforthis.com roast' and enumerates specific outputs (verdict tier, score, security risk, framing, URL), making the verb+resource+scope explicit. It distinguishes itself from siblings like get_verdict by emphasizing the comprehensive nature and persistent result page.

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 does not provide explicit guidance on when to use this tool versus siblings like get_verdict or browse_explore. It lacks 'use this when...' or 'instead of...' statements. The presence of sibling tools makes this a gap, as users must infer the tool's role solely from its name and output list.

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