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

With no annotations provided, the description carries the full burden of behavioral disclosure. It explains that the tool returns text snippets and requires manual integration afterward, which is useful context. However, it doesn't disclose important behavioral traits like whether this is a read-only operation, if it makes external API calls, potential rate limits, or error handling for invalid requests.

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 extremely concise and well-structured with only three sentences, each serving a distinct purpose: trigger conditions, tool limitation, and required follow-up actions. There's zero wasted text, and the most important information (when to use the tool) is front-loaded.

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 annotations and no output schema, the description provides adequate context for a simple tool but has gaps. It explains the tool's purpose and usage well but doesn't describe what the output looks like (format, structure, or content of returned snippets) or address potential limitations or error conditions that would help an agent use 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?

With 100% schema description coverage, the baseline is 3. The description doesn't add any parameter-specific information beyond what's already in the schema (message and searchQuery parameters are fully documented in the schema). No additional syntax, format, or usage details for parameters are provided in the description.

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: 'returns the text snippet for that UI component' when users request new UI components. It specifies the exact trigger conditions (mentions of /ui, /21, /21st, or specific component types) and distinguishes it from sibling tools by focusing on returning component snippets rather than inspiration or logo searches.

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 explicit usage guidelines: 'Use this tool when the user requests a new UI component' with specific trigger examples, and distinguishes it from alternatives by stating 'This tool ONLY returns the text snippet' and requiring follow-up actions. It clearly defines when to use this tool versus other approaches.

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 behavioral disclosure burden. It states that no code is generated, that only the text snippet is returned, and that the agent must edit or add files afterward. It does not cover authentication, limits, or exact return shape, but the key behavioral constraints are disclosed.

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 short and front-loaded with the trigger conditions. There is some redundancy between 'returns the JSON data' and 'ONLY returns the text snippet', but the overall structure is efficient and the post-call instruction 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 two-parameter fetch-like tool with a rich schema and no output schema, this description provides sufficient context: when to use it, what it returns, what it does not do, and what the agent must do afterward. It could be slightly richer on output formatting, but it is largely 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 input schema already documents both required parameters with 100% coverage, so the description adds limited semantic value beyond the schema. The description clarifies that searchQuery is for finding a matching UI component, but this is also reflected in the schema's parameter description.

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 identifies the action as fetching component data and previews from 21st.dev, and it contrasts itself with code generation by stating it does not generate new code. It does not explicitly distinguish itself from the refiner sibling, so it stops short of full differentiation.

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 opens with explicit trigger conditions: 'when the user wants to see component, get inspiration, or /21st'. It does not provide when-not guidance or name alternative tools, but the usage context is clear enough for an agent to select this tool appropriately.

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 to lean on, the description carries the behavioral burden and does well by detailing supported formats, theme variations ('if available'), and the exact structure of results (component name, code, import instructions). It does not cover failure modes or no-result behavior, but the disclosed behavior is sufficient for the agent to anticipate what will happen.

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 well-organized with clear sections for purpose, usage, examples, formats, and output structure. It is slightly longer than strictly necessary because example queries partially repeat the usage triggers, but each section earns its place and the key info is front-loaded in the first sentence.

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 there is no output schema and no annotations, the description does a good job of explaining what the tool returns, including output format options and result fields. However, it mentions 'category filtering' even though the input schema has no category parameter, and it does not explain what happens when a logo is not found, leaving minor but real 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 schema already describes both parameters (format and queries), so the baseline is 3; the description adds significant value by defining what each format returns (TSX/JSX/SVG), providing concrete example query arrays, and showing how command-style inputs map to the queries parameter. This goes beyond the schema's minimal descriptions.

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 precise verb and resource: 'Search and return logos in specified format (JSX, TSX, SVG).' It clearly distinguishes itself from sibling tools (which concern component inspiration, refining, and building) by focusing on logo lookup and output formats. The example queries and command styles reinforce exactly what the tool does.

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 'When to use this tool' section explicitly lists two concrete trigger conditions: user types '/logo' command or asks to add a company logo not in the local project. The phrase 'that's not in the local project' provides a clear when-not-to-use condition, effectively excluding cases where the logo is already available locally.

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