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Search Apple's official developer documentation and video content using advanced RAG technology. Returns relevant content from Apple's technical documentation, frameworks, APIs, design guidelines, and educational resources.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesSearch query for Apple's official developer documentation and video content. Queries must be written in English and focus on technical concepts, APIs, frameworks, features, and version numbers rather than temporal information.
result_countNoNumber of results to return (1-10)

TDQS

A3.5/5.0
Behavior3/5

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

With no annotations, the description carries full burden. It notes the tool 'Returns relevant content' from specific sources, but lacks details on side effects (e.g., read-only nature), rate limits, or result format. The mention of 'advanced RAG technology' adds little behavioral transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise and front-loaded with the core purpose. The phrase 'using advanced RAG technology' is slightly non-essential, but overall every sentence serves to explain scope and output.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple search tool with full parameter coverage, the description adequately states the search scope and return content type. However, it does not clarify the relationship with 'fetch' or describe the result structure, which is acceptable given no output schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema descriptions fully cover both parameters (100% coverage), so the description adds no extra parameter-level meaning. The baseline of 3 applies because the schema already documents query and result_count effectively.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool 'Search Apple's official developer documentation and video content' with a specific verb and resource. This differentiates it from the sibling tool 'fetch', which likely retrieves specific content.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance on when to use this tool versus 'fetch' or any other alternative. The description only states the purpose, with no hints about preferred contexts or exclusions.

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

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TDQS

A3.9/5.0
Disambiguation5/5

fetch and search have clearly distinct purposes: retrieving a specific document by URL versus searching across the content corpus. No overlap or ambiguity exists.

Naming Consistency5/5

Both tool names are single verbs ('fetch', 'search') following a consistent action-oriented pattern. Naming is simple and predictable.

Tool Count3/5

With only two tools, the set feels thin for a documentation server, though each tool is essential and well-scoped. The count is borderline per the calibration guidelines.

Completeness5/5

For a read-only documentation server, fetch and search cover the core workflows: accessing specific content and discovering relevant material. No significant gaps are apparent.