iFun

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

Annotations already cover read-only and non-destructive nature. The description adds the behavioral detail that the tool returns 'full text' and that it is for reading before citing. This adds context beyond annotations without contradiction, contributing valuable transparency.

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, zero filler. The first sentence states the action and source; the second gives explicit usage guidance. Well-structured, front-loaded, and every word 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 tool is simple (one required param, output schema present). The description covers the what, when, and source, and since an output schema exists, return format needn't be described. Minor omissions like error behavior are not significant for this scope, so it is nearly complete.

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 description already fully documents the parameter ('Post id, as returned in a `search` result'). The tool description repeats this same information without adding new semantics. With 100% schema coverage, the description adds minimal value here; 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 states a specific action ('Retrieve the full text') on a specific resource ('one iFun post') and ties it to the id from `search`. It distinguishes from potential alternatives by explicitly referencing search as the source of the id, making the tool's unique role clear.

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 says 'Use this to read a search result in full before citing it,' providing a clear when-to-use condition. It implies when not to use (when you don't have an id from search) but does not name alternative tools like `get_post`. This is nearly explicit guidance, just missing direct 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?

Annotations already declare readOnlyHint=true and destructiveHint=false, covering safety. The description adds only the resource type ('iFun post') but no further behavioral context (e.g., return format, errors, pagination). This meets the minimal bar but adds little beyond 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?

The description is a single, efficient sentence with no waste. It is front-loaded with the action and resource, making it ideal for quick scanning.

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 tool with one parameter, strong annotations, and no output schema, the description is complete enough for an agent to select and invoke it correctly. It covers what, how, and the specific identifier needed.

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 covers the only parameter 'id' with a description, and the description's 'numeric id' restates the schema's integer type. No additional parameter meaning is added, matching 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 specifies the verb ('Get'), the resource ('iFun post'), and the scope ('by its numeric id'), clearly distinguishing it from siblings like random_joke or search. It is specific and 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?

The description implies usage when you have a specific post id, which provides clear context. However, it does not explicitly state when not to use it or mention alternative tools for other use cases, so it lacks explicit 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?

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds a minor nuance ('most recent', 'today's') but no extra behavioral details like rate limits, authentication, or fallback behavior. It is consistent with annotations and sufficient for such a simple read-only 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?

The description is a single, clear sentence that front-loads the action and result. No wasted words, ideal for a simple tool.

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 one optional parameter, no output schema, and clear read-only annotations, the description provides enough context about what it returns (a joke). It doesn't describe output format, but the tool's purpose is obvious. A score of 4 reflects that it is nearly complete for its simplicity, though a bit more detail on the return could be added.

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 provides full documentation for the single 'lang' parameter, including enum values and default (vi). The description adds no additional parameter meaning, but since schema coverage is 100%, the 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 gets iFun's most recent joke, with a specific verb ('Get') and resource ('iFun's most recent joke'). It distinguishes itself from the sibling tool 'random_joke' by emphasizing 'most recent' and 'today's', making the 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?

The description implies the use case: when you want today's joke rather than a random one. It gives clear context about recency but does not explicitly name alternatives or exclusions, though sibling tools like 'random_joke' suggest the contrast.

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 and destructiveHint=false, establishing a safe read operation. The description adds minimal context by naming the source 'iFun' but does not disclose behavior like response format or randomness guarantees. With annotations covering the safety profile, this is adequate but not rich.

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, concise sentence: 'Get a random joke from iFun.' It is front-loaded with the action and resource, and every word earns its place. No unnecessary information.

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 tool with one optional parameter and no output schema, the description is complete enough. It states the primary action and source. It could clarify return format, but that's largely self-evident for a joke. The presence of annotations and schema coverage compensates for any gaps.

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 provides 100% coverage of the single parameter 'lang' with enum values and a clear description. The tool description adds no additional parameter meaning, so the baseline score 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 the tool's function: 'Get a random joke from iFun.' It uses a specific verb and resource, and the word 'random' helps differentiate from sibling tools like 'joke_of_the_day.' However, it does not explicitly name alternative tools, so it's clear but not fully differentiated.

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 no guidance on when to use this tool versus siblings like joke_of_the_day or random_video. It does not mention exclusions or alternatives. The use case is implied by the name and description, but there is no explicit direction.

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 annotations already declare readOnlyHint=true and destructiveHint=false. The description adds the random selection behavior and discloses the output structure (page URL and video file URL), providing useful context beyond the annotations. It could mention more about rate limits or language behavior, but it is adequate.

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, concise sentence that front-loads the operation and clearly states the returned data. Every word earns its place; there is no fluff 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 simple one-optional-parameter tool with good annotations, the description adequately covers the operation and return value. It does not mention the language parameter or alternative tools, but the schema and sibling context fill those gaps. Overall, it is sufficiently complete for the 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?

The input schema covers the only parameter 'lang' with a description, enum, and default value (vi), making schema coverage 100%. The description adds no additional meaning about this parameter, so the baseline 3 applies.

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 ('Get'), names the resource ('random short video'), identifies the source ('from iFun'), and states the exact return values ('page URL and the video file URL'). This clearly distinguishes it from sibling tools like random_joke or get_post.

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?

No explicit guidance is provided on when to use this tool versus alternatives such as random_joke or search. The intended use is implied by the name and description, but there is no mention of alternatives, exclusions, or prerequisites.

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 cover read-only and non-destructive behavior. The description adds a concrete behavioral constraint: 'Returns up to 10 matches.' This is useful context beyond the schema and aligns with the readOnlyHint. No contradictions exist; the added result limit justifies a score above baseline.

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 primary purpose and scope. It includes the result limit without extraneous detail. Every word earns its place; no redundancy or padding.

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 two-parameter search tool with annotations covering safety and an output schema present, the description covers the essential behavior (keyword search, content scope, result limit) and requires no further explanation of return values. The agent has everything needed to call it correctly.

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%, with both parameters (query, lang) documented in the schema. The description does not add any parameter-specific meaning beyond what the schema already provides. Per the rubric, with high coverage the 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 the verb 'Search' and the resource 'iFun', with specific content types (jokes, quotes, fun facts, short videos) and the keyword-driven nature. It is distinguishable from siblings like random_joke or joke_of_the_day, though it doesn't explicitly name them; the scope is implied rather than contrasted.

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 no guidance on when to use this tool versus the sibling tools (e.g., random_joke, joke_of_the_day). It does not mention exclusions or conditions, leaving the agent to infer that keyword-based search is distinct from random retrieval. This is a clear gap.

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