Award score-based XP from a game/activity (separate from study-time XP). Cascades to the leaderboard via DB trigger. Requires sign-in.
| Name | Required | Description | Default |
|---|---|---|---|
| xp | Yes | XP to award (>= 0). | |
| reason | No | Optional human label for analytics. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses side effect ('Cascades to the leaderboard via DB trigger') and auth requirement ('Requires sign-in'). Annotations are consistent and description adds value beyond them.
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 concise, front-loaded sentences with no wasted words. Each sentence contributes essential information.
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?
Covers key effects (leaderboard trigger) and prerequisites (sign-in). No output schema exists, but return value is not critical. Could mention if XP replaces or adds to existing score.
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?
Input schema has 100% description coverage for both parameters. The description does not add new meaning beyond the schema's parameter descriptions, so baseline of 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 clearly states it awards score-based XP from a game/activity, differentiating from study-time XP. This provides a specific verb and resource, but lacks explicit differentiation from sibling tools like 'play_game'.
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?
Implies usage context ('separate from study-time XP', 'Requires sign-in'), but does not explicitly state when to use it vs. alternatives or provide exclusion criteria.
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.