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mohamedaadhil96

LangChain & LlamaIndex Coding Assistant

get_docs

Search official documentation for LangChain, LlamaIndex, and OpenAI libraries to find API references and coding guidance.

Instructions

Search the latest docs for a given query and library. Supports langchain, openai, and llama-index.

Args: query: The query to search for (e.g. "Chroma DB") library: The library to search in (e.g. "langchain")

Returns: Text from the docs

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
libraryYes
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It mentions 'latest docs' implying freshness but doesn't disclose behavioral traits like rate limits, authentication needs, pagination, or error handling. For a search tool with zero annotation coverage, this leaves significant unknowns about its operation.

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 well-structured and concise, with a clear purpose statement, supported libraries list, and separate sections for Args and Returns. Each sentence adds value, though the Returns section could be more informative. It's front-loaded and avoids redundancy.

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

Completeness3/5

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

Given 2 parameters with 0% schema coverage and no output schema, the description provides basic parameter semantics and return type ('Text from the docs'). However, it lacks details on output format, error cases, or behavioral constraints, making it minimally adequate but incomplete for effective use.

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 description coverage is 0%, so the schema provides no parameter details. The description adds basic semantics: 'query' is 'The query to search for' with an example, and 'library' is 'The library to search in' with examples and supported values. This compensates partially but lacks depth on format constraints or library specifics.

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

Purpose4/5

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

The description clearly states the tool's purpose: 'Search the latest docs for a given query and library.' It specifies the verb ('Search'), resource ('docs'), and scope ('latest docs'), and lists supported libraries. However, with no sibling tools, it cannot demonstrate differentiation from alternatives, preventing a perfect score.

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?

The description provides no guidance on when to use this tool versus alternatives, prerequisites, or exclusions. It mentions supported libraries but doesn't explain why or when to choose one over another. Without sibling tools, this is less critical, but the lack of any usage context is a gap.

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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