Auth-only. Personal study trends over a window (default 14 days, max 90): session count, total minutes, accuracy trend (up/down/flat), and top-missed words. Use after a user asks 'how am I trending / am I improving / which words keep tripping me up'.
| Name | Required | Description | Default |
|---|---|---|---|
| days | No | Window size in days (default 14, max 90). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint, destructiveHint, idempotentHint. Description adds 'Auth-only' and window constraints, providing useful behavioral context beyond 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?
Two sentences, front-loaded with key information, no extraneous words.
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 simple read-only tool with one optional parameter and no output schema, the description sufficiently lists return values and constraints, making it complete.
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% and already documents the 'days' parameter with default and max. The description repeats this information without adding new meaning, so baseline score 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 'Personal study trends over a window' and lists specific outputs (session count, total minutes, accuracy trend, top-missed words), distinguishing it from siblings like get_class_session_trends.
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?
Explicitly tells when to use: after user asks about trending, improving, or top-missed words. Does not mention when not to use, but the context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools have clear, distinct purposes with detailed descriptions. A few pairs like study_plan_preview vs get_study_plan_recommendation or get_definition vs explain_word_in_context have subtle overlaps, but descriptions effectively differentiate them.
All tool names use lowercase snake_case with a consistent verb_noun pattern. Some names are longer but follow the same structure. No mixing of conventions, though the variety of verbs is high.
31 tools is on the high side for a vocabulary server. The scope is broad (definition, quizzes, games, progress, parent/tutor features), but many tools are specific, making the set feel heavy. It earns its count but could be trimmed.
The tool surface covers most user needs: learning, testing, progress tracking, parental involvement, and support. Minor gaps like class management or deletion operations exist, but core vocabulary workflows are complete.