Skip to main content
Glama

Search books

search_books
Read-onlyIdempotent

Search Most Recommended Books' human-curated catalog by book title or author name. Returns ranked matches with author, publication year, how many verified people recommend each book, the top recommenders, a sourced quote, and a buy link. Use this when a user asks about a specific book, an author's books, or wants recommendations matching a title they half-remember. For 'who recommends X?' prefer get_book_recommenders; for 'what does person X recommend?' prefer get_person_recommendations.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax results (default 6)
queryYesBook title or author name, e.g. 'Atomic Habits' or 'Cormac McCarthy'

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYes
modeYes
itemsYes
sourceYes

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true, so the safety profile is covered. The description adds valuable context beyond annotations: the catalog is 'human-curated,' results are 'ranked,' and include 'verified people' recommenders. It also discloses the return payload components (quote, buy link). No contradictions with annotations.

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?

Three sentences, front-loading the core action and resource, then listing return values, then providing usage context and alternatives. Every sentence earns its place with no redundant filler or repetition of annotation fields.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 2-parameter search tool with a rich output schema and strong annotations, the description comprehensively covers the tool's purpose, result contents, usage triggers, and sibling differentiation. It also notes the 'half-remembered title' use case, making it complete for an agent to decide when to invoke.

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?

Schema description coverage is 100%, with both 'query' and 'limit' already fully described (including examples and default). The description largely restates the schema's query semantics ('book title or author name') without adding new parameter-level insights. Thus the baseline of 3 applies.

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 opens with a specific verb ('Search') and a clear resource ('Most Recommended Books' human-curated catalog') scoped by 'book title or author name.' It distinguishes itself from siblings by detailing the return fields (ranked matches, author, publication year, recommenders, quote, buy link) and explicitly contrasts with get_book_recommenders and get_person_recommendations.

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?

Provides explicit when-to-use guidance: 'when a user asks about a specific book, an author's books, or wants recommendations matching a title they half-remember.' It also names alternatives for related queries ('who recommends X?' → get_book_recommenders; 'what does person X recommend?' → get_person_recommendations), covering both inclusion and exclusion.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4.5/5.0
Disambiguation5/5

Each tool targets a distinct query type: book-centric recommendations, topic lists, person-centric recommendations, series ordering, summaries, and general search. The overlap between search_books and get_book_recommenders is clarified by their descriptions, so there is no real ambiguity.

Naming Consistency5/5

All tools follow a consistent verb-first pattern: get_ or search_ followed by a descriptive noun. This makes the tool names predictable and easy to remember.

Tool Count5/5

Six tools is well-scoped for a book recommendation server, covering the core user intents without unnecessary bloat. Each tool earns its place and there is no sense of redundancy or missing functionality.

Completeness5/5

The tool set covers the full range of book-related queries: searching, finding recommendations by book or person, curated topic lists, series order, and summaries. There are no obvious gaps that would prevent an agent from answering common user questions.