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by io.github.Embassy-of-the-Free-Mind

Search Translations

search_translations
Read-onlyIdempotent

RETURNS QUOTABLE PASSAGES (page-level snippets + citation URLs), matched by KEYWORD/term. PICK THIS to find a quote or textual evidence on a topic across the whole library. → If the modern word won't literally appear in historical texts, use search_concept (matches by meaning); to list which BOOKS cover a topic use search_library; to dig inside one known book use search_within_book; if the user named an author/work, get_book first (its AI summary is usually the right first read). Query tips: single distinctive terms ("memory palace", "wax tablet") work best; multi-word natural-English queries ("unity of the intellect") may return fewer results because matching is term-based, not phrase-based. Each snippet has a snippet_type — "translation"/"ocr" means it is a verbatim extract from the source text; "summary" means it is AI-generated description (do not quote those as the author's words). Response includes total_matches, returned, and offset for pagination. Cross-cultural tip: for pre-modern or non-Western topics, search source-tradition vocabulary rather than modern English terms — e.g. for seminal economy search "jing" or "bindu" or "istimnāʾ", not "semen retention"; for female homoeroticism search "tribade" or "sahq", not "lesbian". The corpus is indexed via period translations that use tradition-internal terminology.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
langNoISO code of the EDITION to read, e.g. "es". Default "en". Most books have only English — call get_book and read `editions`, or list_books with has_edition, to find the ones that do not. The response always states which edition it served.
limitNoMax results per page (default 20, max 50)
queryYesSearch term — prefer single distinctive concepts ("harmony of the spheres", "active intellect") over long natural-language phrases. Multi-word queries match all terms (not phrase); wrap in "double quotes" for exact phrase.
offsetNoPagination offset (use with limit to page through total_matches; default 0)
book_idNoSearch within a specific book
year_toNo
languageNoFilter by a single original language
languagesNoFilter to any of these languages, e.g. ["Sanskrit", "Arabic", "Chinese"]. Use instead of language when targeting multiple traditions.
year_fromNo
exclude_languagesNoExclude these languages, e.g. ["Latin", "French", "German", "English"] to surface non-Western sources.

TDQS

A4.9/5.0
Behavior5/5

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

Annotations declare readOnlyHint=true and destructiveHint=false; the description reinforces this with non-mutating language ('returns', 'matched'). Critically, it discloses that 'summary' snippets are AI-generated and should not be quoted as the author's words, and that matching is literal term-based — behavioral traits beyond what annotations provide.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is dense but efficient, using a single block with clear 'PICK THIS' guidance and parameter tips. Slightly long for an MCP tool, but every sentence carries distinct value — no redundancy. The structure (purpose → alternatives → query tips → output semantics → cultural tip) is logical.

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?

With 10 parameters (80% schema coverage), the description addresses the most impactful ones: query syntax, pagination via total_matches/returned/offset, edition behavior via response. It covers output types, caveats about AI summaries, and cross-cultural search strategy. The only minor gap is undocumented parameters (year_from/year_to, language filters) left to the schema alone, but this isn't a completeness failure given the description's breadth.

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

Parameters5/5

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

The description explains query semantics in depth (term-based matching, phrase vs. term behavior, language filters via languages vs exclude_languages). It documents 8 of 10 parameters, leaving only year_from/year_to without prose explanation, but these benefit from schema presence. The snippet_type distinction is a semantic gem.

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 specific purpose: returning quotable passages with page-level snippets and citation URLs matched by keyword. It explicitly differentiates from sibling tools by naming search_concept, search_library, search_within_book, and get_book with their distinct purposes, making selection criteria unambiguous.

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 with named alternatives and exclusions (e.g., 'use search_concept if the modern word won't literally appear'), plus concrete query tips (single distinctive terms, double quotes for exact phrases) and a cross-cultural vocabulary tip. This exceeds the bar for usage guidance.

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

A4.5/5.0
Disambiguation4/5

Tools are organized around distinct actions—discover, read, cite, search, contribute—and the descriptions cross-reference each other heavily. The only mild ambiguities are the get_quote/get_quotes pair and the multiple passage-search variants, which overlap in result type but are scoped differently.

Naming Consistency5/5

All tools use snake_case verb_noun names with predictable prefixes: get_* for retrieval, list_* for catalog enumeration, search_* for discovery, and plain verb_noun for contribution actions. Pluralization and compound nouns like get_book_text are minor variations that do not break the pattern.

Tool Count5/5

Fifteen tools is at the upper end of the ideal range, but every tool maps to a distinct step in the library workflow: discovery, reading, citation, search, editions, images, and community contributions. None feels redundant or decorative.

Completeness5/5

The surface covers the full research lifecycle: discovering books, reading them, locating canonical references, citing exact pages, searching by keyword/meaning/within a book, comparing editions, finding images, and contributing findings back. The pipeline from get_book to get_book_text to get_quote provides clear forward paths with no dead ends.

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