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search_agno_docs

Search AGNO documentation by keyword to retrieve relevant excerpts about Agents, Teams, and Workflows. Find implementation guidance for AI agent and multi-agent system development.

Instructions

Search AGNO documentation by keyword and return relevant excerpts.

Args: query: Search keywords (e.g. 'memory storage', 'multi-agent team').

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations provided, so description carries full burden. It discloses that results are 'excerpts' rather than full documents, which is valuable. However, it omits details on result ranking, maximum number of results, or whether searches are fuzzy/exact.

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?

Uses standard docstring format with summary sentence followed by Args block. Front-loaded with purpose; no redundant filler. The colon after 'Args' and clean formatting aids readability.

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?

Appropriate for a single-parameter search tool. With output schema provided, the description correctly avoids redundant return value specification while adequately documenting the input parameter and search scope.

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

Parameters4/5

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

Schema has 0% description coverage (only title 'Query'). The description fully compensates by labeling it 'Search keywords' and providing concrete syntax examples that clarify expected input format and content.

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?

Clear verb ('Search'), resource ('AGNO documentation'), and mechanism ('by keyword'). The phrase 'return relevant excerpts' clarifies the output type. However, it does not explicitly differentiate from siblings like get_agno_page (which likely retrieves full pages by ID).

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?

Provides concrete usage examples ('memory storage', 'multi-agent team') implying suitable query patterns, but lacks explicit when-to-use guidance or comparison with siblings (get_agno_page for specific URLs, list_agno_sections for browsing).

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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