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Glama

Get Book Work

get_book_work
Read-onlyIdempotent

Fetch the canonical Open Library "work" record (the concept of a book across all its editions), by work ID (e.g. "OL45804W"). Returns title, description, first publish date, subjects, and author keys. Use search_books to find a work_id (the W-suffixed key); use get_book for a specific edition by ISBN. (Named get_book_work to avoid colliding with Crossref get_work.)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
work_idYesOpen Library work ID, the W-suffixed identifier (e.g. "OL45804W").

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
titleYesWork title
authorsYesAuthor IDs
work_idYesOpen Library work ID
subjectsYesSubject tags
cover_urlYesURL to cover image
descriptionYesWork description
subject_timesYesTime period subjects
subject_peopleYesPerson subjects
subject_placesYesPlace subjects
open_library_urlYesOpen Library work URL
first_publish_dateYesDate of first publication

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Added

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior. The description adds useful context: it explains what a 'work' represents (concept across editions), lists the returned fields, and notes the W-suffixed id format. While it doesn't disclose additional behavioral traits like pagination or error handling, the annotation coverage is strong and this added context is valuable.

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, each earning its place: the first states the core function, the second provides usage guidance, and the third explains the naming choice. No fluff or redundant repetition of schema details.

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?

Given the low complexity (single required param), rich annotations, and presence of an output schema, the description is fully complete. It covers the tool's purpose, usage guidance, return fields, and relationship to siblings, leaving no meaningful gap for an agent to guess.

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 coverage is 100%, with a clear description of work_id as the W-suffixed identifier. The description reinforces this with an example and the same W-suffix wording, but adds no new semantic information beyond the schema. Baseline 3 is appropriate because the schema already does the heavy lifting.

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 uses a specific verb ('Fetch') and resource ('canonical Open Library work record'), clearly distinguishing it from sibling tools like get_book (edition-specific) and search_books (finding work IDs). It also explains the naming rationale to avoid collision with Crossref get_work, further clarifying its unique purpose.

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?

Explicitly states when to use this tool and directs users to alternatives: 'Use search_books to find a work_id (the W-suffixed key); use get_book for a specific edition by ISBN.' This provides clear context and exclusions, making it easy for an agent to select correctly.

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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TDQS

A4.1/5.0
Disambiguation3/5

Several tool families overlap at the boundaries: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all route questions to the same 5,724 tools, and ask_pipeworx_beta is currently functionally identical to ask_pipeworx. The Polymarket family is large but each member has a fairly distinct role (research vs. edge scan vs. fill risk vs. tracking); the memory trio and book tools are clear.

Naming Consistency3/5

Most tools follow a snake_case verb_noun pattern (get_book, create, search_books, resolve_entity, list_subscriptions), but there are notable exceptions: recall/remember/forget are bare verbs without a domain prefix, ask_pipeworx begins with a verb but doesn't follow the noun-object structure, and ai_visibility_check/generate_llms_txt break the pattern. It's readable and mostly predictable, but not uniform.

Tool Count3/5

35 tools is heavy and exceeds the typical well-scoped range, but the server is a meta-platform exposing a universal data router plus prediction-market analysis, book lookup, memory, subscriptions, and several composite research tools. Each tool appears to earn its place, though the set feels sprawling and would benefit from consolidation of the ask_pipeworx variants.

Completeness4/5

Coverage is thorough within the apparent domains: data lookup has multiple tiers (casual, grounded, deep research, claim validation), the Polymarket workflow is complete from research to edge discovery to fill-risk verification, memory has save/retrieve/delete, and subscriptions have create/list/cancel/pull. Minor gaps exist (e.g., book author search by name only via Open Library key, no direct tool for invoking a specific raw data pack), but nothing that would strand an agent.