analyze_morphology

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

The annotations already mark the tool as readOnly and idempotent. The description adds substantial behavioral context beyond that: default first-analysis behavior, ambiguity count and flag, usage_note codes, Estonian rendering guidance, indeclinable classification, and the input character cap. There is no contradiction with annotations.

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

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

The description is long but effectively structured: a lead statement, a default-vs-all_analyses clarification, a bulleted output-field list, and a targeted usage warning. It could be folded slightly, but the length is justified because most of the parameter and output semantics are not otherwise fully outlined in the visible schema.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a two-parameter analyzer with an output schema, the description is complete. It covers input restrictions (100k chars), output fields and their semantics, machine vs human-readable usage notes, and a caveat about indeclinables that affects downstream inflection. An agent has enough information to call it correctly and reason recursively about its output.

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

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

Schema coverage is 100%, so both text and all_analyses are already documented. The description improves on this by clarifying default behavior ('By default returns the first most likely analysis'), the meaning of True for all_analyses, the 100,000-character input cap, and practical output semantics tied to the boolean parameter.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb and resource: 'Run full morphological analysis on Estonian text.' It then enumerates exactly what is returned (lemma, part-of-speech, grammatical form, root, ending, clitic, compound parts, ambiguity, usage flags), which clearly distinguishes it from narrower siblings like lemmatize or pos_tag.

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

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

The description clearly conveys when to use the tool: when full morphological analysis is needed, with a default single analysis and an optional all_analyses mode. It also gives application guidance around indeclinable words and inflection. It does not explicitly compare against sibling tools like lemmatize or spell_check, so it stops one step short of a 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.