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Get Artwork

get_artwork
Read-onlyIdempotent

Get complete details for an artwork by ID. Returns title, artist, date, medium, dimensions, description, credit line, and high-resolution image.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesARTIC artwork ID (e.g., 27992)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesArtwork ID
dateNoDate of creation
titleYesArtwork title
artistNoArtist display name
mediumNoMedium used (e.g., oil on canvas)
image_idNoARTIC image identifier
image_urlNoURL to high-resolution image
dimensionsNoPhysical dimensions of artwork
credit_lineNoCredit line or acquisition information
descriptionNoDetailed artwork description

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is well covered. The description adds value by enumerating the exact return fields (title, artist, date, medium, dimensions, description, credit line, and high-resolution image), which gives the agent concrete expectations about the tool's output beyond the 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?

The description is two concise sentences that are front-loaded with the core purpose, followed by a clear list of returned fields. Every word earns its place, with no fluff or repetition. It is efficient and well-structured for quick parsing.

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

Completeness4/5

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

The tool has only one parameter and an output schema exists, so the description does not need to explain return formatting. The description adequately covers what the tool does and what it returns for a simple get-by-ID operation. It lacks mention of error cases or special behavior, but given the simplicity, this is not a significant gap.

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?

The schema fully describes the single parameter 'id' with an example and type. Schema description coverage is 100%, so the description need not elaborate on parameters. The description only mentions 'by ID,' which reinforces what the schema already states. No additional semantic meaning is provided beyond the structured schema.

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 clearly states the tool's function: 'Get complete details for an artwork by ID.' It specifies the action (get), the resource (artwork), and the scope (by ID). It also lists the returned fields, making it unmistakably distinct from related tools like get_artist or search_artworks.

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?

The description implies usage context by saying 'by ID,' which indicates the caller must have an artwork ID and need full details. While it doesn't explicitly mention alternatives, the specificity of the purpose provides clear context for when to use this tool. No exclusions or alternate tool references are given, but the context is unambiguous for a get-by-ID tool.

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

A3.8/5.0
Disambiguation2/5

Several clusters of tools heavily overlap: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, and validate_claim all answer natural-language questions over the same underlying sources, and six polymarket tools (bet_research, polymarket_edges, polymarket_arbitrage, polymarket_fill_risk, polymarket_edge_tracker, polymarket_kalshi_spread) have blurry boundaries. The four art museum tools are entirely unrelated to the data-research tools, adding confusion to the set.

Naming Consistency3/5

Names are consistently snake_case and generally readable, but the verb-object pattern is not consistent: bare verbs (remember, forget, recall, subscribe) sit alongside verb-first names (get_artwork, validate_claim, resolve_entity) and noun-first compounds (pipeworx_trending, polymarket_edges, ai_visibility_check). The repeated prefixes (ask_pipeworx, polymarket_) do provide some structure.

Tool Count2/5

At 35 tools, the server is overstuffed. The core Pipeworx data and Polymarket analytics surface alone would justify roughly 20 tools, but memory management, subscription lifecycle, llms.txt generation, npm dependency scanning, claim validation, and Art Institute of Chicago lookups are unrelated additions that push the count well beyond a focused scope.

Completeness4/5

Each functional cluster is fairly complete on its own: memory has remember/recall/forget, subscriptions have subscribe/list/recent_alerts/unsubscribe, data lookup has casual, grounded, deep, and validation modes, and prediction markets cover research, edges, arbitrage, fill risk, tracking, and cross-venue spreads. The issue is not missing capabilities but the lack of a single coherent domain.