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wealthi-ai

wealthi-coach-mcp-server

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by wealthi-ai

Get Assessment Results

get_assessment_results
Read-onlyIdempotent

Fetch a student's recent assessment attempts with scores and dates, paginated for large histories.

Instructions

Retrieve a student's recent quiz/assessment attempts, most recent first.

Reads from Firestore (users/{studentId}/quizAttempts). Paginated since this collection grows unbounded over a student's tenure — always check has_more.

Args:

  • student_id (string): The student's unique identifier.

  • limit (number): Max results to return, 1-50 (default 20).

  • cursor (string, optional): Pagination cursor from a previous call's next_cursor.

Returns: JSON object with schema: { "studentId": string, "results": [ { "attemptId": string, "topic": string, "score": number, // 0-100 "completedAt": string, // ISO 8601 "attemptNumber": number } ], "hasMore": boolean, "nextCursor": string // present only if hasMore is true }

Examples:

  • Use when: "How did this student do on their last few quizzes?" -> default limit

  • Use when: "Show me everything" -> paginate using next_cursor until has_more is false

Error Handling:

  • Returns an empty results array (not an error) if the student has no attempts yet.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
student_idYesThe student's unique identifier (Firebase Auth UID / Supabase user_id — these are the same value across both systems).
limitNoMaximum number of assessment results to return (1-50, default 20).
cursorNoPagination cursor from a previous call's next_cursor field.
Behavior5/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true. The description adds that it reads from Firestore, is paginated, and always check has_more. It also discloses error handling (empty array for no attempts). This significantly enriches the behavioral understanding 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.

Conciseness5/5

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

The description is well-structured with clear sections: main action, data source, pagination notes, args, returns, examples, and error handling. No fluff, every sentence adds value. Front-loaded with the core purpose.

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?

For a tool with 3 parameters (1 required) and no output schema, the description provides a complete picture: data source, pagination mechanism, return schema, examples, and error handling. It covers all necessary context for an agent to use it correctly.

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

Parameters4/5

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

Schema description coverage is 100%, so baseline is 3. The description's Args section repeats parameters but adds useful context: default for limit, optional cursor, and why cursor is used (pagination). It also includes a full return schema, which is not in the structured schema. This adds value beyond the schema.

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 clearly states it retrieves a student's recent quiz/assessment attempts, sorted most recent first. The verb 'Retrieve' and resource 'quiz/assessment attempts' are specific, and it's distinct from sibling tools like get_student_progress or get_coach_context.

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

Usage Guidelines4/5

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

Provides concrete examples of when to use ('How did this student do on their last few quizzes?') and how to paginate for full history. Does not explicitly mention when not to use, but the context is clear enough for an agent to decide.

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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