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Fiveable for AP Students

by io.github.thinkfiveable

Get multiple-choice practice questions

get_practice_questions
Read-onlyIdempotent

Returns original, course-specific multiple-choice practice questions. Free-text topics are matched against Fiveable's course map, so natural phrasing works. Omit topic to get balanced practice across the whole subject, with varied units, skills and stimulus formats. For history, science and language subjects this can return source-based sets — one stimulus with several questions off it — and stimulus images come back as viewable images. This is targeted or mixed practice, distinct from Fiveable's durable adaptive diagnostic.

Every question carries a Question id that supports a saved answer submission for student progress. The recentCorrect and recentAnswered inputs allow the tool to drop to easier question types when a student is missing questions, helping find where understanding breaks down. A returned question set consumes one full-content preview unless existing access covers this practice feature. Moderate cost — roughly 300 tokens per question, more when images are attached.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeYes"exam" requests Fiveable's balanced whole-course practice mix of units, skills and stimulus formats. "topic" drills one scope. "auto" picks exam when no topic is given.auto
tierNoThe tier the student was just working at — pass back the tier from the previous result, along with recentCorrect / recentAnswered, so a student who is still missing comprehension questions drops to vocabulary rather than being handed comprehension again. On its own it pins the level: stimulus = source-based application, comprehension = does the student know the content, vocabulary = does the student know the terms.
limitYesExact maximum number of questions to return, including questions in a stimulus set.
topicNoFree-text topic, e.g. "photosynthesis" or "the American Revolution". Matched against Fiveable course topics, then key terms. Omit for whole-subject mixed practice.
intentNoPrivacy-safe reason for the request. Use explain, quiz, notes, frq, or research; never send the student's raw prompt for analytics.
unitIdNoExact unit id, public id, or slug from get_subject_outline. Use this for broad practice across a unit; do not substitute one topic id as a proxy for the entire unit.
topicIdNoExact topic id from get_subject_outline, if known.
subjectSlugYesFiveable subject slug, e.g. "ap-bio".
recentCorrectNoHow many of the student's recent answers were correct, for automatic tier adjustment.
includeAnswersYesDefaults false so students can attempt questions before seeing the key. Set true only when the student explicitly asks for answers. Use check_practice_answer anonymously or submit_practice_answer when signed in.
questionFormatYes"auto" matches what the subject's own practice UI leads with. "stimulus-set" requests source-based questions; "standalone" requests single questions with no shared source.auto
recentAnsweredNoHow many questions the student recently answered. Needs 3+ before the tier moves.

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

A4.7/5.0
Behavior5/5

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

Despite readOnly/idempotent hints, the description adds important non-obvious behavior: adaptive tier dropping via recentCorrect/recentAnswered, preview-quota consumption, and token cost (roughly 300 tokens per question, more with images). It also discloses stimulus-set behavior and that a Question id enables answer submission.

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 dense paragraphs with front-loaded core purpose, then usage variants, then side effects/cost. No filler; the length is justified by the tool's 12 parameters and the non-obvious quota/cost behavior.

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?

Between the prose and the fully described input schema (100% coverage) plus an existing output schema, an agent has enough to select and invoke the tool: topic modes, answer-key defaults, tier adjustment, preview consumption, and cost are all covered.

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 coverage is 100%, so baseline is 3. The prose adds value by explaining why recentCorrect/recentAnswered matter (drop to easier question types) and that topic matching accepts natural phrasing, going beyond the schema's mechanical descriptions.

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 first sentence nails a specific verb and resource: it 'returns original, course-specific multiple-choice practice questions.' It further disambiguates by saying this is 'targeted or mixed practice, distinct from Fiveable's durable adaptive diagnostic,' so an agent can separate it from diagnostic and exam-result tools.

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?

Gives concrete selection guidance: omit topic for whole-subject balanced practice, pass topic for targeted practice, and notes subject-specific source-based behavior. It explicitly distinguishes this from the adaptive diagnostic, though it stops short of naming the exact sibling to use instead.

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.

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