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Search Ludo docs

searchDocs
Read-onlyIdempotent

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

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

A4.8/5.0
Behavior5/5

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

Beyond the readOnly/idempotent annotations it discloses several non-obvious traits: no credit charge, no job queued, ranking is best-first with weak matches dropped, empty results mean the docs don't cover the topic, and the corpus is the end-user web docs so it may describe UI buttons rather than API parameters. The 503 behavior and non-retry advice are exactly the kind of operational context annotations cannot carry.

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?

Front-loaded with purpose and the primary routing instruction, then progressively adds edge cases (empty results, 503, UI-vs-API caveat). It is dense but long for a two-parameter tool, and the sentence restating `n` (default 3, max 10) duplicates the schema verbatim and could be dropped.

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 exists, so the description carries the return contract itself: ranked sections, `doc`/`section`/`content` fields, a hard cap of n sections, and what an empty list signifies. Combined with the cost/failure disclosures, nothing an agent needs to call this correctly is missing.

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 coverage is 100%, so both params are already documented (including min/max and examples). The description still adds meaning by framing `query` as a plain-language question rather than keywords, and by tying the response's `doc`/`section` fields back into a follow-up getDocs call; it only repeats the `n` default/max already in the 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?

States a specific verb and resource ('Search Ludo's own documentation') plus the return shape ('only the few sections that answer it'), and explicitly contrasts with the sibling it is not ('Start here rather than reading whole documents', getDocs for browsing). An agent can distinguish searchDocs from getDocs without opening either schema.

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?

Gives explicit when-to-use ('before you generate with it', with concrete example questions), when-not/alternative (browse the table of contents via getDocs, re-read a section via getDocs), and a failure-mode fallback ('If it answers 503 ... call getDocs instead rather than retrying in a loop'). It also tells the agent what an empty result means and how to react (rephrase).

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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