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search_functions

Find LSL functions by describing their behavior or using keywords. Returns ranked matches to help you identify the correct function name.

Instructions

Full-text search across LSL function names and descriptions.

Use when you know roughly what a function does but not its exact name. Returns a ranked summary list — call lookup_function for the full record.

Args: query: Keywords or natural language, e.g. "listen channel message" or "set prim texture face". limit: Maximum results to return (default 10, max 25).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
limitNo
Behavior2/5

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

No annotations are provided, so the description fully bears the burden of behavioral disclosure. It mentions 'returns a ranked summary list' but does not describe the search algorithm, ranking criteria, pagination, error handling, or structure of the summary. For a tool with zero annotation coverage, this is insufficient.

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 appropriately sized: a one-line purpose statement, a two-line usage guideline, and two-line parameter descriptions (with examples). Every sentence is necessary and front-loaded with the most important info. No fluff or irrelevant details.

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 the tool has no output schema and no annotations, the description lacks details about the return format (structure of summary list, fields included). It also doesn't mention rate limits, error cases, or behavior when no results found. However, the param descriptions are good and the usage guidance is clear. It is somewhat incomplete but functional.

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?

Schema description coverage is 0%, so the description must compensate. It provides meaningful explanations: for 'query' it says 'Keywords or natural language, e.g. "listen channel message" or "set prim texture face".' for 'limit' it says 'Maximum results to return (default 10, max 25).' These add significant meaning beyond the schema's mere titles and types.

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 states 'Full-text search across LSL function names and descriptions.' It uses specific verb (search) and resource (LSL function names/descriptions) and explicitly distinguishes from sibling 'lookup_function' by saying it returns a ranked summary list and to use lookup_function for the full record.

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 says 'Use when you know roughly what a function does but not its exact name.' and 'returns a ranked summary list — call lookup_function for the full record.' This explicitly tells when to use and when not to use, with an alternative named.

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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