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file_support_ticket

File a real human-followup support ticket on behalf of the signed-in user. Use this when the user reports a bug, account lockout, complaint about a tutor, or anything Sparkle/the agent cannot resolve from data. The ticket is emailed to the support team and a confirmation is sent to the user with a 1-business-day SLA. Vocab Voyage is completely free, so there is nothing to bill — never raise pricing, plans or upgrades. Categories: billing (legacy, use account instead), bug, account, complaint, feedback, other. Requires sign-in.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
summaryYesOne-line description of the issue (what the user needs).
categoryYesIssue category. Use 'bug' for crashes/data loss, 'account' for lockouts/access or any account/access question, 'complaint' for tutor/quality issues, 'feedback' for feature requests. 'billing' is legacy and unused — the product is free.
conversation_snippetNoOptional: last few turns of the conversation for context.

TDQS

A4.7/5.0
Behavior5/5

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

Beyond the annotations (readOnlyHint=false, etc.), the description reveals key side effects: 'The ticket is emailed to the support team and a confirmation is sent to the user with a 1-business-day SLA.' It also states 'Requires sign-in' and the pricing policy, giving full context on what happens and required conditions.

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

Conciseness5/5

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

The description is front-loaded with the core purpose, then flows through usage, side effects, policy, categories, and auth in a logical order. Every sentence adds unique, valuable information; there is no redundancy or fluff.

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

Completeness5/5

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

Given the tool's moderate complexity and the absence of an output schema, the description covers all necessary context: when to use, what happens after filing (email, SLA, confirmation), category handling, and authentication requirements. Combined with the rich parameter schema, this is fully complete for an agent to invoke correctly.

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

Parameters3/5

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

Schema description coverage is 100%, so the schema already fully documents each parameter with details and guidance (e.g., category enum descriptions). The prose description largely repeats this information (e.g., billing legacy note) without adding new technical specifics about parameter values or formats.

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

Purpose5/5

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: 'File a real human-followup support ticket on behalf of the signed-in user.' It clearly distinguishes this tool from the sibling tools by focusing on human follow-up and support escalation, making its purpose unmistakable.

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

Usage Guidelines5/5

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

It explicitly states when to use the tool: 'Use this when the user reports a bug, account lockout, complaint about a tutor, or anything Sparkle/the agent cannot resolve from data.' It also provides a category guidance note—'billing (legacy, use account instead)'—which helps avoid misuse.

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

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TDQS

A3.7/5.0
Disambiguation4/5

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.

Naming Consistency4/5

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.

Tool Count3/5

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.

Completeness4/5

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.