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

There are no annotations, so the description carries the responsibility for behavioral disclosure. It accurately states the core read behavior and title-based scoping. However, it does not describe the return format, behavior when a title is not found, or whether the returned section contains nested content. The description 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, front-loaded sentence that states the operation, the resource, and illustrative examples. There is no wasted wording, and it is appropriately sized for a simple one-parameter retrieval 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 required parameter and no output schema, the description covers the essential selection and invocation needs: what it returns and how to identify the section. The only minor gap is the lack of explicit detail about the returned content or error behavior, but this does not block correct invocation.

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 fully describes the title parameter and its case-insensitivity, so the baseline is 3. The description adds value by giving concrete examples of top-level titles ('Accordion', 'Installation', 'Themes'), which helps the agent understand what counts as a valid input.

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 ('Returns') and a specific resource ('official Skeleton documentation section') qualified by top-level title. Concrete examples like 'Accordion', 'Installation', and 'Themes' make the tool's scope unmistakable and clearly distinguish it from the search-oriented sibling.

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 clearly implies when to use this tool: when you need a specific Skeleton documentation section identified by its exact top-level title. It does not explicitly contrast with search_skeleton_docs or skeleton_svelte_guidance, but the 'specific section by title' framing gives 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?

With no annotations, the description carries the burden, and it clearly says the tool searches official documentation and returns the most relevant top-level sections. It does not discuss external network access or detail limits beyond what the schema already states, but for a read-only search tool the behavior is sufficiently 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 two sentences with no filler. The action and result are front-loaded, followed by a compact list of intended use cases. 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 search tool with fully documented parameters, the description is nearly complete: it states the resource, return type, and use cases. It could be improved by explaining how it relates to get_skeleton_section and skeleton_svelte_guidance, but nothing essential to invoking it correctly is missing.

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 adds no parameter-level detail beyond the schema, but the schema already explains query examples and the limit's min/max/default, so no compensation is needed.

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 and resource: it searches the official Skeleton documentation and returns top-level sections. It does not explicitly distinguish itself from the sibling tools, but the output type and listed topics make its purpose distinct enough for selection.

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 gives an explicit list of use cases: Svelte components, Tailwind utility classes, themes, installation, or APIs. It does not mention exclusions or alternatives like get_skeleton_section, but it provides enough context for when this search tool is appropriate.

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 behavioral disclosure burden. It usefully states that the tool returns excerpts from official documentation and explicitly says it 'does not generate unverified APIs,' which sets accurate expectations about output reliability. It does not mention potential limitations such as excerpt length or search freshness, but the provided traits are meaningful.

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 with no filler. The core behavior is front-loaded, and the negative guarantee about not generating unverified APIs is a valuable, compact addition.

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 tool, the description covers what it does and what it returns (implementation-oriented excerpts). There is no output schema, but the description partially compensates by describing the return type. However, it could benefit from clarifying the exact form of the excerpts or what to do when no relevant documentation is found.

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 single 'task' parameter is fully covered by the schema, including an example. The description adds no parameter-specific detail beyond the schema, so the baseline score of 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 clearly states the tool's verb ('Finds'), resource ('official Skeleton documentation'), and intended scope ('most relevant to a Svelte UI task'). It distinguishes itself by emphasizing Svelte-orientation and implementation excerpts, though it does not explicitly contrast with its siblings.

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 intended use is implied: for Svelte UI tasks needing relevant official documentation excerpts. However, there is no explicit guidance about when to prefer this tool over search_skeleton_docs or get_skeleton_section, and no exclusions or alternative conditions are mentioned.

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