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Fiveable for AP Students

by io.github.thinkfiveable

Get subject outline

get_subject_outline
Read-onlyIdempotent

Returns the full unit and topic outline for one AP subject, including every study guide slug in each unit. Provides the course map for study planning and individual guide retrieval. Moderate cost — roughly 2-5k tokens depending on subject size.

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.
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

A4.2/5.0
Behavior4/5

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

Beyond the annotations, which already declare read-only, idempotent, and non-destructive behavior, the description discloses a moderate token cost (2-5k depending on subject size) and the specific content of the response. This adds helpful context for the agent to manage expectations.

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 sentences with no filler; the core return value is front-loaded, followed by a practical cost note. The description is efficiently structured and every sentence contributes to the agent's understanding.

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

Completeness4/5

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

Given the tool only has two parameters, a complete output schema, and safety annotations, the description covers the key payload and cost behavior. It does not explicitly handle alternative selection among the many retrieval siblings, but that is a minor omission given the other structured signals.

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 both parameters are fully documented in the schema. The description adds little new meaning beyond framing subjectSlug as representing 'one AP subject' and noting the returned study guide slugs, which is ancillary rather than necessary.

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 the tool returns the full unit and topic outline for one AP subject, with every study guide slug in each unit. This distinguishes it from siblings like get_unit_overview or get_study_guide by emphasizing the whole-subject scope and its role as a course map.

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?

It provides clear context on when to use this tool: for study planning and to locate individual study guides. However, it does not explicitly name alternatives or give exclusions, so it falls just short of a full routing rule.

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