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Get Livonian inflection table

livonian_get_inflections
Read-onlyIdempotent

Fetch the full declension (nouns) or conjugation (verbs) table for a word identified by a search result's inflection handle (entry_id + word_class) — the exact case, number, tense, not a guessed ending. Use this only when a search ran without inline forms, or to fetch a match a broad search left un-expanded. Never a first call — the handle values only come from livonian_search results, and a default search already returns each match's table inline, so calling this afterwards just re-fetches what you have.

Returns Markdown — a nominal gets one case × {singular, plural} table; a verb gets a table per mood/tense (person × {affirmative, negative}, the negation auxiliary folded into the negative) plus its principal-parts and participle lists — or a clean not-found message. (Grammatical labels are normalised to English; Livonian forms stay verbatim.) The same table rides along as structuredContent with the shape {"result": } per the declared outputSchema — switch on result.category ('nominal' | 'verbal' | 'not_found') before reading the body. Results are cached server-side (repeats are instant) and calls are rate limited — on a rate-limit error, wait a few seconds and retry. Table content is from livonian.tech (CC BY-SA 4.0 — attribute if republished).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
entry_idYesThe word id from a search result's inflection handle. Accepts a number or a digit-string (e.g. 17746 or "17746").
word_classYesThe word-class code from a search result's inflection handle (e.g. 's' = noun, 'adj' = adjective, 'vi' = intransitive verb, 'vt' = transitive verb).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • changedInput schema / title
      Previous value: -"get_inflectionsArguments"New value: +"livonian_get_inflectionsArguments"
    • changedOutput schema / title
      Previous value: -"get_inflectionsOutput"New value: +"livonian_get_inflectionsOutput"
  2. First observed

TDQS

A4.8/5.0
Behavior5/5

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

Beyond the readOnly/idempotent/openWorld annotations, the description discloses output modality (Markdown vs structuredContent), shape of both, table composition (case × number, mood/tense, negation auxiliary folding), and operational traits: server-side caching, rate limiting with a retry instruction, and CC BY-SA licensing. This is exactly the extra context annotations cannot carry.

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 purpose and the never-a-first-call warning before the return-format detail. Dense and mostly waste-free, though the second sentence restates the 'not a first call' point at some length and the output-format sentence is heavy with parentheticals.

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?

For a two-parameter read tool with an output schema, annotations, and full schema coverage, the description covers everything an agent needs: provenance of the handle, fallback semantics, return shape, and error/rate-limit behavior. Nothing material 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 each parameter is already documented with examples, so the baseline is 3. The description adds the crucial provenance detail that both values come from a search result's inflection handle, tying the parameters to their only valid source.

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 (Fetch) and resource (full declension/conjugation table) and pins the input to a search result's inflection handle (entry_id + word_class). It is immediately distinguishable from livonian_search, livonian_romanize and livonian_deromanize.

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 states when to use it ('only when a search ran without inline forms, or to fetch a match a broad search left un-expanded') and when not to ('Never a first call', 'calling this afterwards just re-fetches what you have'). It also names the upstream tool that produces the handle, which is the alternative an agent might otherwise reach for.

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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