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analyze_morphology

Read-onlyIdempotent

Analyze Estonian text morphologically: return lemma, part-of-speech, grammatical form, root, ending, clitic, compound parts, ambiguity info, and usage notes per word.

Instructions

Run full morphological analysis on Estonian text.

For each word returns lemma(s), part-of-speech, grammatical form, root, ending, clitic, compound parts, ambiguity info, and a usage note flagging archaic / foreign / abbreviation / interjection / proper-noun cases. By default returns the first (most likely) analysis per word; set all_analyses=True to return every ambiguous analysis.

Each word's response includes:

  • lemma, partofspeech, form, root, ending, clitic, root_tokens

  • analyses_count: how many alternative analyses Vabamorf produced for this surface form (>1 means the word is morphologically ambiguous)

  • is_ambiguous: shorthand for analyses_count > 1

  • usage_note: machine code (None if neutral) — "archaic" / "foreign" / "abbreviation" / "interjection" / "proper-noun"

  • usage_note_estonian: human-readable Estonian rendering of the same flag (quote this verbatim in Estonian replies; do NOT translate the English usage_note yourself)

  • indeclinable: True for words that stay in base form when used attributively (lexical indeclinables like täis, and -tud/-nud past participles like tuntud) — i.e. they do NOT take the noun's case ending in agreement. Use this before inflecting a noun phrase so you don't wrongly decline an invariant adjective.

Input is capped at 100,000 characters.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
textYesEstonian text to analyse morphologically.
all_analysesNoReturn every ambiguous analysis per word instead of only the most likely one.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

Annotations already declare readOnlyHint and idempotentHint, but the description adds valuable behavioral details: a 100,000-character input cap, default behavior (first analysis), and the effect of all_analyses parameter. It also explains output fields like usage_note and indeclinable, providing transparency beyond structured fields.

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 well-structured with bullet points and front-loaded purpose. It is somewhat lengthy but every sentence adds necessary detail (e.g., output fields, usage notes, indeclinable explanation). Could be slightly more concise but remains efficient.

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?

Given the tool's complexity (morphological analysis with multiple outputs) and the existence of an output schema, the description fully covers input constraints, parameter behavior, and output field semantics. No gaps are evident.

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?

Schema coverage is 100% with descriptions for both parameters. The description adds extra meaning: for all_analyses, it explains when to set it true; for the overall tool, it details output fields that depend on parameters. This adds significant value beyond the schema.

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 it 'runs full morphological analysis on Estonian text,' listing specific outputs (lemma, POS, form, root, etc.). It distinguishes itself from sibling tools like lemmatize or pos_tag by offering comprehensive analysis rather than a single feature.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for full morphological insight but does not explicitly state when to use vs. alternatives or when not to use. It provides clear context on what it returns, allowing inference of appropriate use cases.

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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