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

ReadOnlyHint annotation already signals a non-mutating operation, and the description adds meaningful behavioral context by stating that results are derived from capture_word and log_interaction events and are frequency-ranked. It doesn't describe output shape or empty-result behavior, but this is minor given the read-only, aggregated nature of the tool.

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?

Two sentences, front-loaded with the core definition and followed by an actionable use-case statement. Every clause earns its place and no redundant material is present.

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?

The tool is simple (no required params, no nested objects, no output schema), and the description covers the source data, computation window, ranking, and intended use. The schema handles parameter details, so the description is complete for agent selection and invocation.

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 description coverage is 100%: lang, limit, and lookback_days all have descriptive text including defaults and matching behavior. The description adds no parameter-specific information, so 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?

Description opens with the specific action 'Get' and clearly defines the resource: 'the user's most actively encountered target-language words... ranked by frequency over a lookback window.' It distinguishes itself from sibling tools by explicitly sourcing from 'past capture_word + log_interaction events' and highlighting the frequency-rank aggregation.

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?

Provides explicit usage guidance with 'Use to surface frontier words... when they ask what should I learn next or when you want context-aware suggestions.' This is clear when-to-use context, though it does not name alternative tools or state when not to use this tool.

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