check_compound_familiarity

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

Annotations already declare readOnlyHint: true and idempotentHint: true, establishing safety and idempotency. The description adds behavioral details: input capped at 100k characters, use of a fastText model, and the diagnostic (non-authoritative) nature of output, which go beyond the 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 well-structured: it front-loads the main purpose, then explains technical details, output interpretation, and limits. While slightly long, every section adds value, and there is no waste. A 4 reflects good clarity with minor room for trimming.

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?

Given the tool's complexity (fastText model, diagnostic logic), the description adequately covers how the tool works, how to interpret results, and limitations (legitimate OOV compounds). The presence of an output schema is noted, so the description doesn't need to detail return values. Score 4 reflects sufficient completeness.

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?

Only one parameter 'text' with schema description 'Estonian text whose compound nouns are checked for calque / translationese risk.' Schema coverage is 100%, so description adds minimal extra meaning beyond the schema. Baseline 3 is appropriate.

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 clearly states it is a 'fastText-based diagnostic for compound-noun familiarity in Estonian'. It specifies the key outputs (top fastText neighbours, top_score, neighbour_quality, is_suspect with reasons) and distinguishes this tool from siblings like check_compounds and analyze_morphology by focusing on calque-risk detection.

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 provides explicit guidance on interpreting results ('semantically coherent neighbours mean the compound is fine; neighbours that recycle the input's morphemes or are junk tokens mean a likely coinage') and notes the tool is diagnostic. However, it does not explicitly compare to sibling tools or state when to use this over alternatives.

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