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Search the Livonian dictionary

livonian_search
Read-onlyIdempotent

Look a word up in the real Livonian–Estonian–Latvian dictionary and return only attested content, so translations are grounded, not invented.

Search a meaning (in English/Latvian/Estonian) to find the Livonian headword, or a Livonian word to confirm it exists and read its sense, part of speech and examples. See the query and search_language parameter docs for how to phrase a query. By default each match's full inflection table is returned inline, so one call usually suffices; on a broad query only the first N tables expand (the rest are listed as handles to fetch with livonian_get_inflections). Returns Markdown plus the same result as structuredContent matching the declared outputSchema.

Results are cached server-side, so repeating a query is instant and free; a first-time query reaches the live dictionary and calls are rate limited — on a rate-limit error, wait a few seconds and retry instead of re-issuing immediately. Dictionary content is from livonian.tech (CC BY-SA 4.0 — attribute if republished).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesA SINGLE content word, not a phrase. Exactly one word per call — even with several candidates or synonyms in mind, search them one at a time ('see', then 'look'), never combined into one query like 'see look'. Drop function words and infinitive markers — search 'to water' as 'water', 'the sea' as 'sea'. The dictionary matches one attested headword, so a multi-word query often returns nothing even when the word exists; search the main word first, then refine. May be Livonian, Latvian, Estonian, or English (e.g. 'jarā', 'away', 'sea'). Matching is bidirectional. An inflected Livonian form (search_language='liv') is resolved to its dictionary lemma automatically when the form is known — the result says so when that happened.
max_formsNoOptional override for how many inflection tables to expand this call (0–12). Raise it to pull more tables in ONE call on a broad query, or set a small value to keep a broad query cheap. On an uncached query each table is fetched sequentially with polite pacing toward the upstream, so a high value on a cold broad query is slow — the bound limits upstream fan-out, not just response size. Omit to use the server's default cap.
include_formsNoWhen true (default), each match's full inflection table is returned INLINE — usable cases/tenses in ONE call, no follow-up livonian_get_inflections. Set false to get just the headword handles + glosses: a cheap way to SCREEN several candidate words or synonyms (which exist? which sense?) before spending forms on the one you pick. Bounded by a per-search cap — use max_forms to raise or lower it for this call.
search_languageNoLanguage your query word is in — selects which language the search matches against: 'eng' (default), 'liv', 'lat', or 'est'. For English→Livonian translation, keep 'eng'. Glosses are in English.eng

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
foundYesFalse when nothing matched.
queryYes
sourceNoErnštreits, Valts (ed. in chief), Viitso, Tiit-Rein, Vāvere, Signis, Damberg, Pētõr, Kurpniece, Milda, Balodis, Uldis, Tuisk, Tuuli, Kūla, Gita, Tomingas, Marili, Soosaar Sven-Erik, Sedláčková, Anna & Jurgenovskis, Toms. 2024. Livonian lexicographic database. Riga: University of Latvia Livonian Institute. https://livonian.tech/ (CC BY-SA 4.0: https://creativecommons.org/licenses/by-sa/4.0/) Adapted: reformatted and condensed from the original.
entriesNoStructured dictionary entries: headword, pronunciation, part of speech, paradigm anchors, and senses with example sentences.
handlesNo
languageYes
resolved_fromNoThe original inflected query when search_method='lemma_index'; empty on a direct match.
search_methodNoHow the match was found: 'direct' = the query itself matched; 'lemma_index' = the query was an inflected Livonian form, resolved to its dictionary lemma via the cached paradigm index and re-searched.direct
resolved_lemmaNoThe dictionary lemma actually searched when search_method='lemma_index'; empty on a direct match.
forms_truncatedNoHow many handles did NOT get an inline table because the per-search cap was reached. Refine the query or call livonian_get_inflections.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed4 schema fields changed
    • changedOutput schema / $defs / NominalParadigm / properties / source / default
      Previous value: -"Ernštreits, Valts (ed. in chief), Viitso, Tiit-Rein, Kurpniece, Milda & Vāvere, Signis. 2024. Livonian morphology database. Riga: University of Latvia Livonian Institute. https://livonian.tech/ (CC BY-SA 4.0)"New value: +"Ernštreits, Valts (ed. in chief), Viitso, Tiit-Rein, Kurpniece, Milda & Vāvere, Signis. 2024. Livonian morphology database. Riga: University of Latvia Livonian Institute. https://livonian.tech/ (CC BY-SA 4.0: https://creativecommons.org/licenses/by-sa/4.0/) Adapted: reformatted and condensed from the original."
    • changedOutput schema / $defs / ParadigmNotFound / properties / source / default
      Previous value: -"Ernštreits, Valts (ed. in chief), Viitso, Tiit-Rein, Kurpniece, Milda & Vāvere, Signis. 2024. Livonian morphology database. Riga: University of Latvia Livonian Institute. https://livonian.tech/ (CC BY-SA 4.0)"New value: +"Ernštreits, Valts (ed. in chief), Viitso, Tiit-Rein, Kurpniece, Milda & Vāvere, Signis. 2024. Livonian morphology database. Riga: University of Latvia Livonian Institute. https://livonian.tech/ (CC BY-SA 4.0: https://creativecommons.org/licenses/by-sa/4.0/) Adapted: reformatted and condensed from the original."
    • changedOutput schema / $defs / VerbalParadigm / properties / source / default
      Previous value: -"Ernštreits, Valts (ed. in chief), Viitso, Tiit-Rein, Kurpniece, Milda & Vāvere, Signis. 2024. Livonian morphology database. Riga: University of Latvia Livonian Institute. https://livonian.tech/ (CC BY-SA 4.0)"New value: +"Ernštreits, Valts (ed. in chief), Viitso, Tiit-Rein, Kurpniece, Milda & Vāvere, Signis. 2024. Livonian morphology database. Riga: University of Latvia Livonian Institute. https://livonian.tech/ (CC BY-SA 4.0: https://creativecommons.org/licenses/by-sa/4.0/) Adapted: reformatted and condensed from the original."
    • changedOutput schema / properties / source / default
      Previous value: -"Ernštreits, Valts (ed. in chief), Viitso, Tiit-Rein, Vāvere, Signis, Damberg, Pētõr, Kurpniece, Milda, Balodis, Uldis, Tuisk, Tuuli, Kūla, Gita, Tomingas, Marili, Soosaar Sven-Erik, Sedláčková, Anna & Jurgenovskis, Toms. 2024. Livonian lexicographic database. Riga: University of Latvia Livonian Institute. https://livonian.tech/ (CC BY-SA 4.0)"New value: +"Ernštreits, Valts (ed. in chief), Viitso, Tiit-Rein, Vāvere, Signis, Damberg, Pētõr, Kurpniece, Milda, Balodis, Uldis, Tuisk, Tuuli, Kūla, Gita, Tomingas, Marili, Soosaar Sven-Erik, Sedláčková, Anna & Jurgenovskis, Toms. 2024. Livonian lexicographic database. Riga: University of Latvia Livonian Institute. https://livonian.tech/ (CC BY-SA 4.0: https://creativecommons.org/licenses/by-sa/4.0/) Adapted: reformatted and condensed from the original."
  2. Added

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already cover read-only/idempotent/open-world safety, but the description adds substantial behavior beyond them: server-side caching (repeat queries free), upstream rate limiting with explicit retry-after-a-few-seconds guidance rather than immediate re-issue, sequential polite pacing on cold broad queries, and CC BY-SA attribution. Return format (Markdown plus structuredContent per outputSchema) is also disclosed.

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 purpose and grounded-content guarantee, then usage, then cost/rate behavior. Dense and mostly waste-free, though it partially restates the schema's own include_forms/max_forms wording and is longer than strictly necessary for an agent that still must open the parameter docs.

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, the description needn't enumerate return fields, and it still tells the agent the two output forms, the caching/rate-limit lifecycle, the fallback tool for unexpanded tables, and the licensing constraint. Nothing material for correct invocation is missing.

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 coverage is 100%, and the description defers to the parameter docs, but it still adds real semantics the schema alone wouldn't convey: why queries must be a single content word, that the dictionary matches one attested lemma so phrases silently fail, that matching is bidirectional, and that inflected Livonian forms auto-resolve to a lemma with a signal in the result. The max_forms 'limits upstream fan-out, not just response size' note likewise explains the cost tradeoff.

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 — look up a word in the real Livonian–Estonian–Latvian dictionary and return attested content. It also clarifies the bidirectional capability (meaning→headword, Livonian word→sense/POS/examples), which cleanly separates it from livonian_get_inflections, anglo_search, and other sibling lexicons.

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 explains when one call suffices (full inflection tables returned inline by default) and names the alternative for the remaining cases (handles fetched later via livonian_get_inflections). It also gives a concrete screening strategy — set include_forms=false to check several candidates cheaply before spending forms on one.

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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