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searchDocs

Search Ludo's own documentation with a plain-language question and get back only the few sections that answer it - the fastest way to learn how a feature is meant to be used before you generate with it (how to pick a sprite animation mode or model, how margins behave, what something costs, known limitations). Start here rather than reading whole documents. Each result carries doc and section, which you can pass straight to getDocs to re-read that section, and the section's full markdown content. Results are best first; weak matches are left out, so an empty results list means the documentation does not cover the question - rephrase it, or call getDocs with no parameters to browse the table of contents. This is the same documentation the Ludo web app shows its users, so it occasionally describes buttons rather than parameters; the substance applies to the API and MCP surfaces just the same. Returns up to n sections (default 3, max 10). If it answers 503 the search backend is briefly unavailable: call getDocs instead rather than retrying in a loop. This is a free discovery endpoint: it does not charge credits and does not queue a job.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nNoMaximum number of sections to return. Defaults to 3.
queryYesWhat you want to know, in plain language, e.g. "how do I keep a sprite animation's colors consistent" or "what does a 3D model cost".

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.6/5.0
Behavior5/5

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

With no annotations, the description carries the full behavioral burden and handles it thoroughly: weak matches are omitted, empty results mean the documentation doesn't cover the question, results include doc/section/full markdown, 503 means the backend is unavailable, and the endpoint is free and does not queue a job. It also flags that the docs occasionally describe buttons rather than parameters.

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 long but appropriately packed with necessary behavioral and fallback information. It is front-loaded with purpose and actionable guidance, though a few clauses are slightly redundant ('Start here rather than reading whole documents' restates the fastest-way point).

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?

Despite having no output schema, the description fully explains return shape (doc, section, content), ordering, empty results, n defaults, and error fallback. An agent has everything needed to invoke the tool correctly and interpret the response.

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 100%, so the baseline is 3. The description reinforces that query is a plain-language question and n caps the number of sections, but it does not add meaningful parameter semantics beyond what the schema already states.

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?

States a specific verb ('Search') and resource ('Ludo's own documentation'), and explains the search is question-driven and returns only the few sections that answer it. It clearly differentiates from getDocs by saying results carry doc/section identifiers to pass to getDocs for re-reading.

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?

Explicitly tells the agent when to start here ('before you generate', 'Start here rather than reading whole documents') and what to do when results are empty or the backend returns 503, including naming getDocs as the fallback. This is direct and actionable 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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