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Search operators

search_operators
Read-only

Search the embedded operator knowledge base by keyword to find the right TouchDesigner operator before creating nodes. Get ranked results with name, family, and summary, fully offline.

Instructions

Search the embedded operator knowledge base (629 operators) by keyword — name, family or description — ranked by relevance, fully offline. Use it to discover the right operator before creating nodes instead of guessing a type (e.g. 'what sends DMX?', 'particle', 'corner pin'). Returns name, family and a one-line summary per hit. Pass semantic:true to re-rank by embedding similarity (needs an LLM endpoint; falls back to keyword).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesWhat you're looking for — words from a name, family, or description (e.g. 'blur edge', 'audio spectrum', 'instance geometry').
limitNoMax results to return.
semanticNoOpt-in: re-rank keyword candidates by embedding similarity via the configured LLM endpoint (TDMCP_LLM_BASE_URL / _MODEL, Ollama by default). Better for fuzzy/conceptual queries. Falls back to keyword ranking if the endpoint is unavailable — the default (false) needs nothing.
Behavior5/5

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

Annotations declare readOnlyHint and openWorldHint. The description adds value by explaining offline operation, fallback behavior for semantic search, and what is returned (name, family, summary). No contradictions.

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?

Two sentences plus a return summary; front-loaded with core action. Every sentence is informative and concise.

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?

No output schema, but description explains return format (name, family, one-line summary). Covers parameters, usage context, and a key detail (629 operators). Sufficient for an agent to use effectively.

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 covers all parameters with descriptions, but the description adds context: query examples, limit as max results, and semantic re-ranking details with fallback. This goes beyond schema.

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 it searches an operator knowledge base by keyword, with examples like 'what sends DMX?'. It distinguishes from sibling tools, which are primarily creation or manipulation tools, not search.

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

Usage Guidelines4/5

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

Explicitly says 'Use it to discover the right operator before creating nodes instead of guessing a type', providing clear when-to-use guidance and giving concrete examples. It doesn't explicitly state when not to use, but the context is clear enough.

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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