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fuzzy_find_and_traverse

Find and rank schema.org entities from natural language, tolerating typos and alternative names. Returns bounded entity context with relationship IDs; use get_entity for full detail. The optional detail argument is summary (for each hit: id, type, name, url, the start of the description and the match score) or full (every property and relationship). A client on protocol 2026-07-28 or later gets summary unless it asks for full; an older client gets full unless it asks for summary.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeNo
limitNo
queryYes
detailNo
weightsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
countYes
itemsYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / detail
      Added value: +{
      +  "enum": [
      +    "summary",
      +    "full"
      +  ],
      +  "type": "string"
      +}
  2. Changed6 schema fields changed
    • removedInput schema / properties / limit / description
      Removed value: -"Optional: maximum ranked entities to return (default 5, maximum 10)"
    • removedInput schema / properties / query / description
      Removed value: -"Search terms (e.g., \"AI optimisation services\", \"schema markup articles\")"
    • removedInput schema / properties / type / description
      Removed value: -"Optional: filter by entity type (Organization, Service, Article, Person, WebPage, Question)"
    • removedInput schema / properties / weights / description
      Removed value: -"Optional: Custom weight multipliers for ranking"
    • removedInput schema / properties / weights / properties / entityTypes / description
      Removed value: -"Entity type multipliers (e.g., {\"Service\": 2.0, \"Article\": 1.0, \"Question\": 2.0})"
    • removedInput schema / properties / weights / properties / predicates / description
      Removed value: -"Predicate weight multipliers (e.g., {\"name\": 3.0, \"about\": 1.5})"
  3. First observed

TDQS

A3.9/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: it discloses the bounded return shape (id, type, name, url, description start, match score), that relationship IDs are included, and the protocol-version-dependent default for the detail argument, which the schema does not encode. It omits permissions, error behavior, and how the 'traverse' half of the name actually works.

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 sentences, front-loaded with purpose, then return shape, then the argument semantics; no filler. The final sentence is dense but each clause is load-bearing because it encodes defaults absent from the schema.

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 return values need not be re-explained, and the description covers the detail modes well. However, for a 5-parameter tool with nested objects, the weights parameter and the traversal implied by the tool's name are unaddressed, leaving the agent under-informed for non-default invocations.

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%, so the description must carry parameter meaning, and it only fully explains 'detail' (summary vs full contents). 'type', 'limit', and especially 'weights' (a nested predicates/entityTypes object) are left entirely unexplained, leaving a large semantic gap.

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+resource ('Find and rank schema.org entities from natural language') plus the fuzzy-matching behavior ('tolerating typos and alternative names'), which cleanly separates it from the exact-type sibling find_by_type. It also names the sibling get_entity and explains why you would call that instead.

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

Usage Guidelines4/5

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

Explicitly routes the agent: 'use get_entity for full detail' when bounded context with relationship IDs is not enough, and explains which detail mode a caller will get. It does not address when to prefer find_by_type or traverse_path over this tool, so guidance is clear but not exhaustive.

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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