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TopImpressionists Art Search & Quotation

Search passages by meaning (articles, museums, artists, artworks)

search_sections_semantically
Read-onlyIdempotent

Semantic search of the texts of our site: returns the sections that answer the question best, by meaning rather than shared words, each WHOLE (section_text is never cut), from the requested models - "article" (our articles: how reproductions are made, policies, art history), "museum", "artist", "artwork" (their descriptions / biographies); default all models indexed on this server. Each result: model, object_pk (use it with the matching get_detail_* tool), object_title, object_url, category_code (articles), section_heading, section_text, is_faq_question, score (cosine; higher is closer). Ask in a full sentence; any language works (the texts are in English). Sections are packed best first into about 9,000 characters: sections_omitted_for_size says how many more matched. Use it to answer a question from what our texts say; to find a work, artist or museum by name or keywords, use search_fts; to find the objects a text is about, use search_objects_semantically. Error index_unavailable: fall back to the search_* full-text tools.

Input Schema

NameRequiredDescriptionDefault
limitNoMaximum number of sections (1-10, default 5).
queryYesThe question or text to find passages for (up to 2000 characters).
modelsNoWhich texts to search (default: every model indexed on this server).
languageNoSite language code (2 letters, e.g. "en", "fr"). Default "en".
category_codeNoOptional article category filter (Support / Website for service and policy questions); applies to articles only.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.9/5.0
Behavior5/5

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

The annotations already establish that this is a read-only, idempotent, non-destructive search. Beyond that, the description discloses that section_text is never cut, results are packed best-first into about 9,000 characters, sections_omitted_for_size reports additional matches, and index_unavailable has a fallback path.

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 dense but front-loaded, leading immediately with the tool's purpose and then layering in models, result fields, alternatives, packing behavior, and error fallback. Every clause carries operational information; there is no filler.

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?

Although there is no output schema, the description enumerates the result fields and explains packing/truncation via sections_omitted_for_size. It also covers model scope, query style, language behavior, sibling routing, and the index_unavailable fallback, making it complete for this complexity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all five parameters. The description still adds useful meaning: query should be a full sentence and may be in any language, the model types are explained by content, and category_code is limited to articles with Support/Website emphasized for service and policy questions.

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 states a specific verb and resource: semantic search over the site's texts, returning sections by meaning rather than shared words. It clearly distinguishes this from search_fts and search_objects_semantically by explaining what each alternative is for.

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?

It gives explicit usage guidance: use it to answer a question from what the site's texts say, use search_fts to find a work/artist/museum by name or keywords, and use search_objects_semantically to find the objects a text is about. It also names the index_unavailable error and the correct fallback to full-text tools.

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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