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quipu_hybrid_search

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Combine SPARQL constraints with vector similarity search using a natural-language query or precomputed embedding, pushing simple type filters into the vector index for filtered ANN retrieval.

Instructions

Combined SPARQL + vector similarity search with predicate pushdown. Accepts a pre-computed embedding or natural-language query. Simple type constraints (e.g. ?s a ) are pushed into the vector index for O(log n) filtered ANN.

Input Schema

NameRequiredDescriptionDefault
limitNoMaximum results (default: 10)
queryNoNatural language search query (auto-embedded when EmbeddingProvider is attached)
sparqlNoSPARQL SELECT query returning entity IRIs in the first variable. Simple type patterns (e.g. ?s a <Type>) enable predicate pushdown.
valid_atNoPoint-in-time for temporal filtering (ISO-8601)
embeddingNoPre-computed query embedding vector (f32 array). Takes precedence over query.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.17.0

TDQS

A3.5/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false and openWorldHint=true, so the safety profile is covered. The description adds real behavioral value by disclosing that only simple type constraints are pushed into the ANN index (so complex filter shapes degrade) and that the filtered path is O(log n). It omits cost/preconditions for the embedding path and the result ordering.

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?

Three tight sentences, front-loaded with what the tool is, then accepted inputs, then the pushdown constraint. No filler, though the O(log n) claim is more marketing than decision-relevant for an agent.

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?

There is no output schema, so the description should clarify what comes back; it only indirectly implies entity IRIs via the SPARQL schema text, and never states whether scores are returned or how results are ranked. For a tool with two alternative input modes and a conditional embedding path, that is a meaningful remaining gap.

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 the baseline is 3. The description earns slightly more by tying the sparql parameter's pushdown benefit to a concrete pattern shape (e.g. ?s a <Type>) and by framing embedding and query as interchangeable inputs, reinforcing the precedence rule the schema already states.

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 verb and composite resource: combined SPARQL + vector similarity search, plus the distinguishing mechanism (predicate pushdown). An agent can distinguish it from a pure SPARQL or pure vector tool, though it never names a specific sibling such as quipu_search or quipu_query to sharpen the contrast.

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

Usage Guidelines3/5

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

Usage is implied rather than stated: the mention of 'combined' search and pushdown hints that this tool is for filtered semantic retrieval, and 'simple type constraints' implies a boundary. But there is no explicit when-to-use, when-not, or named alternative among the many search siblings, and no mention that an EmbeddingProvider must be attached for the query path.

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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