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LearnUs local MCP server

learnus_download_file

Download a previously discovered LearnUs file ID into the configured local LearnUS directory when the user explicitly asks. Creates a local copy without overwriting.

Instructions

Downloads one previously discovered LearnUs fileId into the configured local LearnUS directory. Use only when the user explicitly asks to download that file. Prefer this Tool over browser download for supported fileIds. It reads remote LearnUs data but creates a local file without overwriting; it does not modify LearnUs. Do not pass URLs or guessed IDs. Browser fallback is allowed only when MCP reports the file/capability unsupported or explicit visual interaction is required.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fileIdYesOpaque file ID returned by learnus_list_files, learnus_get_assignment or learnus_get_announcement.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.6/5.0
Behavior4/5

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

Adds real context beyond annotations: it explains why readOnlyHint=false (it creates a local file) while clarifying that remote LearnUs data is not modified, and it discloses no-overwrite semantics, which a caller cannot infer from the schema. It stops short of covering auth prerequisites and rate/error behavior, so it is strong but not exhaustive.

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?

Front-loaded with the action and scope, then layered guidance (preference, side effects, input constraint, fallback) in discrete sentences. Slightly long at six sentences, but each one carries a distinct rule rather than restating structured fields.

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 single-parameter tool with no output schema, the description covers purpose, preconditions, side effects, input constraints and fallback routing. Everything an agent needs to invoke it correctly and to know its limits is present.

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 already 100% and the fileId description names the producing tools, so the baseline is 3. The description goes further by constraining acceptable input ('Do not pass URLs or guessed IDs'), which prevents a common misuse the schema alone does not forbid.

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?

States a specific verb (downloads) and resource (a previously discovered LearnUs fileId into the configured local directory), which cleanly distinguishes it from retrieval siblings like learnus_list_files. An agent can tell immediately that this is the local-materialization tool rather than a metadata reader.

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

Usage Guidelines5/5

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

Explicit when-to-use ('Use only when the user explicitly asks to download that file'), an explicit alternative ('Prefer this Tool over browser download'), and an explicit condition for the fallback ('only when MCP reports the file/capability unsupported or explicit visual interaction is required'). Both the preferred tool and the excluded path are named.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.