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Fiveable for AP Students

Review my completed exam results

get_exam_results
Read-onlyIdempotent

Read an owned completed exam using attemptId, or safely check a submitted exam using submissionId. Supply exactly one. Pending or partial grading returns status only, never unfinished scores or feedback. Honors practice resets and cannot dispatch scoring, finalize submissions or retrieve active exam content.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
attemptIdNo
submissionIdNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
textNoReadable tool result text for clients that consume structured output.
statusYesOperation status: completed, pending, partial, failed, unavailable, or a domain-specific outcome.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already mark the tool as read-only, idempotent, and non-destructive, and the description reinforces this with 'safely check' and 'never unfinished scores or feedback.' It adds valuable edge-case transparency around pending/partial grading and the honors practice reset limitation, going well beyond what the annotations alone provide.

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?

Two tightly packed sentences front-load the core operation before addressing edge cases. Every clause adds meaningful information, with no repetition of the title and no filler.

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?

The description covers invocation modes, identifier constraints, result availability behavior, and the honors-practice limitation. Combined with the existing output schema and read-only/idempotent annotations, an agent has everything needed to invoke this tool correctly.

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

Parameters5/5

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

With 0% schema description coverage, the description carries the full semantic burden and succeeds: it explains when to use attemptId versus submissionId and enforces the mutual exclusivity rule with 'Supply exactly one.' It also conveys the ownership condition ('owned completed exam') that the raw schema cannot express.

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 'Read' and clearly scopes the tool to 'an owned completed exam' via attemptId or 'a submitted exam' via submissionId, establishing two distinct invocation modes. It also adds non-obvious behavioral details about pending/partial grading and honors practice, which further defines what the tool does and does not return.

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?

The description explicitly instructs the agent to supply exactly one identifier and maps each parameter to its appropriate scenario: attemptId for owned completed exams and submissionId for submitted exams. It also warns that pending or partial grading returns status only, preventing unrealistic expectations. It does not name alternative sibling tools, but the usage context is clear.

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

A3.9/5.0
Disambiguation4/5

Most tools target clearly distinct resources and actions, but a few close pairs exist, such as check_practice_answer vs. submit_practice_answer and get_content_sections vs. get_study_guide. Descriptions clarify the boundaries, yet the sheer number of similar get_* and list_* tools adds some selection risk.

Naming Consistency5/5

All tool names follow a consistent snake_case verb_noun pattern, with verbs like get_, list_, create_, submit_, score_, check_, and update_. The get_my_* and list_my_* conventions for user-specific data are also applied predictably.

Tool Count2/5

With 37 tools, the server is well above the 25-tool threshold for a coherent surface and will be heavy for an agent to navigate. The broad platform scope explains some of the count, but many tools could be consolidated or grouped without losing capability.

Completeness4/5

The tool set covers the major student workflows: content study, MCQ practice, FRQ scoring, diagnostics, study plans, key terms, cheatsheets, exams, assignments, and progress tracking. Minor gaps exist, such as no study plan deletion and no MCP-based exam or assignment submission, but these appear to be deliberate platform boundary limitations.