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Get Learning Unit

get_learning_unit
Read-only

One course whole: its row, prerequisites and corequisites, aliases, terms offered, articulation statements and comparable members — each linked course resolved or stated unresolved, never guessed — plus the transfer frameworks it maps to.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
learning_unit_idYesA learning unit id from learning_units or get_checklist

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.5/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnlyHint=true), so the bar for added context is met by the disclosure that each linked course is 'resolved or stated unresolved — never guessed,' which tells the agent to expect explicit gaps rather than fabricated links. This is a genuine behavioral trait beyond the annotations. It stops short of 5 because nothing is said about response shape, size caps, or pagination.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

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

A single dense sentence, front-loaded with the resource identity ('One course whole') followed by the returned contents. Every clause maps to a return element, so little is wasted, though the long em-dash list is heavier than strictly necessary.

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?

There is no output schema, so the description correctly carries the burden of enumerating return contents, and it does so comprehensively for a one-parameter read tool. The only gap is the absence of usage context relative to sibling retrieval tools, which is minor given the simplicity of the input.

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 coverage is 100%; the single parameter learning_unit_id is fully documented in the schema, including its source ('from learning_units or get_checklist') and an example value. The description adds no further parameter meaning. Baseline 3 is appropriate when the schema carries the full burden.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific resource — a single 'learning unit' (course) — and enumerates exactly what it returns: row, prerequisites, corequisites, aliases, terms offered, articulation statements, comparable members, and transfer frameworks. It is clearly distinguishable from the sibling learning_units (list) by the 'One course whole' framing. It lacks an explicit verb and never names the sibling it is not, keeping it just short of 5.

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

Usage Guidelines2/5

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

The description gives no guidance on when to use this tool versus alternatives such as learning_units or get_checklist, and states no prerequisites or exclusions. The only routing hint (where the ID comes from) lives in the schema, not the description. Usage must be inferred entirely from the name.

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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