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RTFD (Read The F*****g Docs)

by aserper

zig_docs

Search official Zig programming language documentation to find information about language features, standard library functions, memory management, error handling, and build system details.

Instructions

        Search Zig programming language documentation.

        USE THIS WHEN: You need information about Zig language features, syntax, stdlib, or concepts.

        BEST FOR: Learning Zig language specifics and finding relevant documentation sections.
        Searches the official Zig documentation (ziglang.org/documentation/master/) and returns
        matching sections with titles, summaries, and relevance scores.

        Good for queries about:
        - Language features (e.g., "comptime", "async", "optionals")
        - Standard library (e.g., "ArrayList", "HashMap", "allocators")
        - Memory management (e.g., "allocator", "defer", "errdefer")
        - Error handling (e.g., "error sets", "try", "catch")
        - Build system (e.g., "build.zig", "zig build")

        NOT SUITABLE FOR: Third-party Zig packages (use GitHub provider for that)

        Args:
            query: Search keywords (e.g., "comptime", "async", "ArrayList", "error handling")

        Returns:
            JSON with matching documentation sections, relevance scores, and source URL

        Example: zig_docs("comptime") → Returns sections about compile-time code execution
        

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
Behavior4/5

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 effectively describes what the tool does (searches documentation and returns matching sections with titles, summaries, relevance scores, and source URL), though it doesn't mention potential limitations like rate limits, authentication needs, or pagination. However, it clearly states the scope (official documentation only) and what to expect in returns.

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

Conciseness5/5

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

The description is well-structured with clear sections (purpose, usage guidelines, examples, parameters, returns, and example), front-loading key information. Every sentence adds value without redundancy, making it efficient and easy to parse despite its comprehensive coverage.

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

Completeness5/5

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

Given the tool's moderate complexity (single parameter, no output schema, no annotations), the description is highly complete. It covers purpose, usage guidelines, behavioral traits, parameter details, return format, and an example, providing all necessary context for an AI agent to understand and invoke the tool correctly without relying on structured fields.

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

Parameters5/5

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

The schema description coverage is 0%, so the description must fully compensate. It provides a dedicated 'Args' section explaining the single parameter 'query' as 'Search keywords' with concrete examples (e.g., 'comptime', 'async', 'ArrayList', 'error handling'), adding significant meaning beyond the bare schema. The example usage further clarifies parameter semantics.

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 searches Zig programming language documentation, specifying the exact resource (official Zig documentation at ziglang.org/documentation/master/) and distinguishing it from sibling tools that search other documentation sources like GitHub, Docker, or package registries. The verb 'search' is specific and the scope is well-defined.

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

Usage Guidelines5/5

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

The description includes explicit 'USE THIS WHEN' and 'BEST FOR' sections that detail when to use this tool (for Zig language features, syntax, stdlib, or concepts) and 'NOT SUITABLE FOR' that explicitly names an alternative (GitHub provider for third-party Zig packages). It also provides a bulleted list of good query examples, giving clear contextual guidance.

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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