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campus_export

Export selected CSMAR or CNRDS data through an authorized campus browser session and save the downloaded file locally for validation.

Instructions

Click the selected export/download button and retain any browser export locally.

query_note must document table, fields, filters, date range and format. No automatic query splitting or limit evasion. wait_seconds is 0–30. For async packaging, inspect the job page or call campus_downloads; don't resubmit. Files get checksums and provenance manifests; their contents are not returned. A received file still needs sample/full, format and coverage validation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
refYes
providerYes
query_noteYes
wait_secondsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.6/5.0
Behavior4/5

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

The description adds significant behavioral details beyond annotations: query_note requirements, wait_seconds range (0–30), async packaging handling (inspect job page or call campus_downloads, don't resubmit), and that files are retained with checksums and provenance manifests but contents are not returned. It also notes that received files need validation. This is rich context, though it doesn't mention permissions or reversibility.

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?

The description is front-loaded with the main action, then follows with key constraints and caveats. It is reasonably concise, though some sentences (e.g., about validation) could be integrated more tersely.

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

Completeness3/5

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

For a mutation tool with no output schema and incomplete parameter documentation, the description covers important behavioral aspects like async handling and file retention. However, it omits details about provider and ref, and doesn't describe the return value or failure modes. Adequate but with clear gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With schema description coverage at 0%, the description must compensate. It only partially does: query_note semantics are explained ('must document table, fields, filters, date range and format') and wait_seconds range is given (0–30). But provider and ref are not described at all, leaving two of four parameters undocumented.

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 action: click the selected export/download button and retain the browser export locally. This is a clear verb+resource, though the phrasing ('selected') implies a prior selection step handled by sibling tools like campus_act or campus_open, which isn't explicitly stated.

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 gives clear context for when to use it (clicking the selected export button) and provides alternatives for async packaging: inspect the job page or call campus_downloads instead of resubmitting. It doesn't explicitly list when-not-to-use, but the guidance is strong.

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