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Fiveable for AP Students

by io.github.thinkfiveable

Get a key term

get_key_term
Read-onlyIdempotent

Returns the full definition, context and related terms for one AP key term. Use when a student asks "what does X mean" for AP vocabulary. Cheap — usually under 1k tokens.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
intentNoPrivacy-safe reason for the request. Use explain, quiz, notes, frq, or research; never send the student's raw prompt for analytics.
termSlugYesKey term slug or the term itself, e.g. "natural-selection".
subjectSlugYesFiveable subject slug, e.g. "ap-bio" or "apush". Use list_subjects to find it.

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

A4.3/5.0
Behavior4/5

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

Annotations already cover readOnly, idempotent, and non-destructive behavior. The description adds value by disclosing the content of the response (definition, context, related terms) and the cost profile ('Cheap — usually under 1k tokens'), which helps an agent weigh this against heavier alternatives.

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 two tight sentences, front-loaded with what the tool does, followed by when to use it and a cost note. No filler or repetition of schema details; every sentence serves a distinct 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 simple read-only getter with a rich output schema, full annotation coverage, and complete parameter descriptions, this is sufficient. The description covers purpose, use case, response contents, and cost—nothing important is missing for correct selection and invocation.

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 termSlug, subjectSlug, and intent. The description adds no parameter-level detail beyond the schema, which is acceptable at the baseline of 3 given the high coverage.

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 states a specific verb and resource ('Returns the full definition, context and related terms for one AP key term') and explicitly names the intended use case (student asks 'what does X mean'). The word 'one' distinguishes it from list_key_terms, and the definition clearly differentiates it from search_content or get_cheatsheet.

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 gives a clear, concrete trigger: 'Use when a student asks what does X mean for AP vocabulary.' It does not explicitly name alternatives to avoid, but the use case is specific enough that an agent can decide when to invoke this tool over siblings.

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.

Resources