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Look a Latgalian word up

latgalian_search
Read-onlyIdempotent

Look a Latgalian word up on Wiktionary and return its senses plus full declension/conjugation tables — attested content, not invented. Any form of the word works; an inflected query is resolved to its lemma automatically via previously cached paradigms and the result notes the resolution. With search_language='eng' the query is an English word instead: the result lists its per-sense Latgalian equivalents (the translations block) plus their expanded entries. Returns Markdown plus the same result as structuredContent matching the declared outputSchema.

Results are cached server-side; first-time queries reach the live upstream politely and calls are rate limited — on a rate-limit error, wait a few seconds and retry. Content is from en.wiktionary.org (CC BY-SA 4.0 — attribute and share alike if republished).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesThe word to look up, in the language search_language names. Latgalian (default): a SINGLE Latgalian word, any form — an inflected form ('akmiņa') is resolved to its lemma ('akmiņs') automatically via cached paradigms, and the result says so; diacritics are optional once a paradigm is cached ('akmins' finds 'akmiņs'). English (search_language='eng'): the English word whose Latgalian equivalents you want — multiword entries like 'apple tree' work.
max_formsNoOptional override for how many inflection tables to expand this call (0–12). On an uncached query each table is one politely paced upstream fetch, so high values on cold queries are slow. Omit for the server default.
include_formsNoWhen true (default), each match's full declension/conjugation table is returned INLINE — usable cases/tenses in ONE call, no follow-up latgalian_get_inflections. Set false for a cheap screen of which entries exist. Bounded by a per-search cap — use max_forms to adjust per call. For eng queries this governs the expanded Latgalian entries; the per-sense translations list itself is always returned.
search_languageNoLanguage the query word is in: 'ltg' (default) looks the Latgalian word up directly; 'eng' finds the Latgalian equivalents of an English word (per-sense, from Wiktionary's translation tables) and returns their full entries. Glosses are in English either way.ltg

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
foundYesFalse when nothing matched. For an eng query, True means Latgalian translations were found — entries may still be empty when none of them could be expanded (see translations).
queryYes
sourceNoWiktionary, the free dictionary (en.wiktionary.org), Latgalian entries. Wikimedia Foundation. Text available under CC BY-SA 4.0; attribution and share-alike required when republishing. (CC BY-SA 4.0)
entriesNo
handlesNo
languageYes
translationsNoPopulated only for eng queries (always [] for ltg): the Latgalian terms each English sense translates to, in sense order. Entries/handles below are the expanded dictionary entries of those terms.
resolved_fromNoThe original inflected query when resolved; else empty. ltg queries only — always empty for eng results.
search_methodNoHow the match was found: 'direct' = the query itself matched; 'lemma_index' = an inflected form resolved via a previously cached paradigm; 'translations' = an English query resolved via Wiktionary translation tables.direct
resolved_lemmaNoThe lemma actually searched when resolved; else empty. ltg queries only — always empty for eng results.
forms_truncatedNoHow many handles did NOT get an inline table because the per-search cap was reached.
translations_truncatedNoHow many distinct translated lemmas were NOT expanded into entries because the per-search expansion cap was reached (they still appear under translations).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already declare readOnly/idempotent/openWorld, and the description adds genuinely new behavior: server-side caching, polite upstream pacing, rate-limit errors with a retry instruction, automatic lemma resolution via cached paradigms, dual Markdown+structuredContent output, and a CC BY-SA attribution obligation.

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?

Front-loaded with the core action and result, and each sentence carries operational information. However, the 'eng' mode and caching behavior are explained in both the description and the schema, so there is some redundancy that slightly dilutes efficiency.

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 an output schema present, return values need not be re-explained; the description still covers caching, rate limits, retry guidance, licensing, and the lemma-resolution behavior. Nothing an agent needs to invoke it correctly is missing.

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%, so the schema already carries the parameter semantics; the description largely restates them. It adds only marginal detail, such as warning that high max_forms on cold queries is slow, which the schema also notes. Baseline 3 is appropriate when the schema 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?

States a specific verb (look up) and resource (a Latgalian word on Wiktionary) and enumerates the return payload (senses plus declension/conjugation tables). It also distinguishes itself from sibling latgalian_get_inflections by noting that tables are returned inline so no follow-up call is needed.

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 documents the two modes via search_language ('ltg' direct lookup vs 'eng' reverse translation search) and when to prefer each. It names the alternative tool (latgalian_get_inflections) and gives a when-not condition (set include_forms=false for a cheap screen instead of pulling full tables).

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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