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Search the OnMind knowledge base using full-text, hybrid, or vector search. Retrieve relevant cards with scores and snippets for questions about OnMind products, methods, and code.

Instructions

BÚSQUEDA PRIMARIA en la base de conocimiento OnMind. Úsala PRIMERA para cualquier pregunta sobre: OnMind-PUB, OnMind-XDB, OnMind-CMS, OnMind-WDB, OnMind-ARK, OnMind-EPI, OnMind-DAI, Método OnMind, ABCode, CloudOps, DevOps, código, arquitectura, productos OnMind. Busca en título, descripción, tags y cuerpo completo (BM25 Orama). Devuelve cards con score y snippet. NO uses búsqueda web hasta agotar esta herramienta.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
qNoFree-text query (Orama full-text / hybrid)
modeNoOverride search mode for this call: fulltext | hybrid | vector (hybrid/vector need RAG_EMBEDDINGS=1)
siteNoLimit to one site name
tagsNoAll of these tags must match
limitNoMax results (default 20)
inBodyNoAlso search markdown body (default true)
offsetNoPagination offset
notableNoOnly notable entries when true
categoryNoCategory facet (e.g. devops, dreams)
languageNoLanguage code, e.g. es or en
visibilityNopublic (default) | protected | all
Behavior3/5

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

With no annotations, the description carries the full burden. It mentions the search algorithm (BM25 Orama) and return format (cards with score and snippet), but lacks details on auth, rate limits, or side effects. It is adequate but not rich.

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 concise with three sentences in Spanish, front-loaded with purpose. Every sentence adds value: primary usage, content scope, and search behavior.

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 11 parameters and no output schema, the description could provide more detail on result pagination or structure. It briefly mentions cards with score and snippet but omits default modes or ordering. Adequate but not fully complete.

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?

The schema has 100% parameter description coverage, so the description adds little beyond stating the search scope. It does not explain parameter interactions or syntax, meeting the baseline expectation.

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 the tool is for primary search in the OnMind knowledge base, listing specific topics (OnMind-PUB, etc.) and search fields (title, description, tags, full body). This distinguishes it from sibling tools like list_sites or get_entry.

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 explicitly instructs to use this tool first for any OnMind question and not to resort to web search until this tool is exhausted. This provides clear when-to-use and when-not-to-use 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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