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search_knowledge

Find information in your private knowledge base by combining semantic meaning with exact keyword matching, returning source links and relevance scores.

Instructions

Búsqueda híbrida en las fuentes scrapeadas y lo capturado de conexiones: semántica (sentido) + por palabra exacta (nombres propios, IDs, fechas, números). Devuelve chunks con url, source_md_path, score (similitud semántica, None si solo matcheó por palabra) y match.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
top_kNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It does disclose meaningful behavior: hybrid semantic/keyword retrieval and, valuably, the score semantics (None when only a keyword match occurred). However it omits operational constraints such as result limits, permissions, or how scoring/ranking is bounded.

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?

Two sentences, front-loaded with the core purpose and with the retrieval modes and return shape following. Dense but efficient, with essentially no filler; it could be tightened slightly but every clause carries information.

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?

An output schema exists, so the return-value explanation is a bonus rather than a requirement. For a two-parameter search tool the description covers what it does and returns, but leaves out the when-to-use guidance and the top_k parameter, which is the main completeness gap.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 0% and neither parameter is named in the description. The aside about exact-word matching for 'proper names, IDs, dates, numbers' indirectly hints at what query content works well, but top_k is entirely undocumented and there is no explicit query-format guidance, so the gap is not compensated.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific action and resource: hybrid search over scraped sources plus captured connections, and names both retrieval modes (semantic + exact word). This is far more than a restatement of the name, though it does not explicitly differentiate itself from any sibling (none of the siblings are competing search tools, so the practical risk is low).

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

Usage Guidelines2/5

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

The description explains how the search works but never says when to reach for it versus alternatives like list_sources, read_file, or vault_overview. There are no exclusions, no prerequisites, and no guidance on choosing between this and other retrieval paths, so the agent must infer usage.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.