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Recommend books from titles

recommend_from_titles
Read-only

Give Siftivo a few books someone liked, by title, and get books like them. Titles are resolved against the catalog first; anything that does not resolve is reported back rather than guessed at.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
titlesYesBook titles, optionally "Title by Author"
isFictionNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
Behavior4/5

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

Annotations declare readOnlyHint=true and destructiveHint=false, covering safety. The description adds valuable behavioral context: titles are resolved against the catalog first, and unresolved titles are reported rather than guessed. This goes beyond the annotations and clarifies error handling.

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?

Two sentences with no filler; the main action is front-loaded and the behavioral caveat follows naturally. Every sentence earns its place and the description is appropriately sized.

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?

For a 3-parameter tool with no output schema, the description covers input semantics and resolution behavior but omits the meaning of limit and isFiction, and does not describe the response structure. It is adequate for basic usage but not fully complete.

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 description coverage is low at 33%, with only 'titles' having an inline description. The description clarifies the core 'titles' parameter (liked books) and resolution behavior, but it adds no meaning to 'limit' or 'isFiction'. With low coverage, the description should have compensated more, especially for output limit and fiction filtering.

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?

The description clearly states the action: provide liked book titles and get similar books. The 'by title' input and catalog resolution distinguish it from recommend_from_description, though it does not explicitly name the alternative.

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?

The description implies usage when you have known liked titles ('Give Siftivo a few books someone liked'), but it does not state when to avoid this tool or mention alternatives such as recommend_from_description or what_to_read_next. No exclusions or preconditions are provided.

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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