emojihub

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states what the tool does without mentioning behavioral traits like whether it's read-only, if there are rate limits, error handling, or output format. For a tool with no annotations, this is insufficient 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?

The description is appropriately sized and front-loaded: the first sentence states the core purpose, followed by relevant examples. Every sentence earns its place by clarifying the tool's function without unnecessary details, making it efficient for agent comprehension.

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 low complexity (1 parameter, no output schema, no annotations), the description is minimally complete. It explains what the tool does and provides examples, but lacks details on output format, error cases, or sibling tool differentiation. This is adequate but has clear gaps in context.

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 100% description coverage, so the schema already documents the 'category' parameter fully. The description adds example categories (e.g., 'smileys-and-people'), which provides some semantic context beyond the schema, but doesn't elaborate on format or constraints. This meets 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 clearly states the tool's purpose: 'Get all emojis in a given category.' It specifies the verb ('Get') and resource ('emojis'), and provides example categories to clarify scope. However, it doesn't explicitly differentiate from sibling tools like 'get_by_group' or 'random_emoji', which would require a 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 provides no guidance on when to use this tool versus alternatives. It lists example categories but doesn't mention sibling tools or contexts where this tool is preferred over 'get_by_group' or 'random_emoji'. This leaves usage decisions ambiguous for the agent.

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 full burden for behavioral disclosure. It describes what the tool does but doesn't address important behavioral aspects like whether this is a read-only operation, what format the output takes, error handling, or rate limits. The description is functional but lacks operational context.

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 perfectly concise - a single sentence stating the purpose followed by helpful examples. Every word earns its place with zero waste or redundancy. The structure is front-loaded with the core functionality.

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 read operation with one parameter and no output schema, the description is adequate but minimal. It explains what the tool does but doesn't address return format, error cases, or how results are structured. Given the simplicity of the tool, it meets minimum requirements but could provide more operational context.

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 schema already fully documents the single 'group' parameter. The description adds value by providing concrete examples of valid group slugs ('face-positive', 'face-negative', etc.), but doesn't add semantic meaning beyond what the schema provides. Baseline 3 is appropriate when schema does the heavy lifting.

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 ('Get') and resource ('all emojis in a given group'), making the purpose unambiguous. It distinguishes from 'get_by_category' by specifying groups rather than categories, but doesn't explicitly contrast with 'random_emoji'.

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 through the example groups provided, suggesting this tool is for retrieving emojis by specific group types. However, it doesn't explicitly state when to use this versus 'get_by_category' or 'random_emoji', nor does it provide exclusion criteria.

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 full burden but only states what the tool does without behavioral details. It doesn't disclose whether this is a read-only operation, if it has rate limits, authentication requirements, or what the return format looks like (e.g., single emoji vs. data structure).

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 that directly states the tool's purpose with zero wasted words. It's appropriately sized for a simple tool and front-loads the essential information without any structural issues.

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 zero-parameter tool with no output schema, the description is minimally adequate but lacks completeness. It doesn't explain the return value (e.g., what 'get a random emoji' actually returns—just the emoji character, or a JSON object with metadata?), and with no annotations, more behavioral context would be helpful for proper agent usage.

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 0 parameters with 100% schema description coverage, so no parameter documentation is needed. The description appropriately doesn't discuss parameters, earning a baseline score of 4 for not adding unnecessary information beyond what the schema already covers perfectly.

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 action ('Get') and resource ('a random emoji from the EmojiHub API'), making the purpose immediately understandable. It doesn't explicitly differentiate from sibling tools like 'get_by_category' or 'get_by_group', which would require mentioning it returns completely random emojis without filtering criteria.

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 guidance is provided on when to use this tool versus alternatives. The description doesn't mention its siblings ('get_by_category' and 'get_by_group') or explain that this tool should be used when no specific category or group filtering is needed, leaving usage context unclear.

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