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Glama

workload_analysis

Read-onlyIdempotent

Analyzes a student's upcoming coursework load over a chosen number of days, combining Moodle counts, points, quizzes, and overdue items with heuristic effort estimates.

Instructions

Workload for the next days days. facts are Moodle data (counts per course and per day, points, quizzes, overdue); estimates are nexus-mcp heuristics for hours of effort and are explicitly not instructor estimates.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
daysNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A3.5/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive, so the safety profile is covered. The description adds genuinely valuable context beyond that: it separates ground-truth Moodle `facts` (counts, points, quizzes, overdue) from `estimates` that are nexus-mcp heuristics and explicitly not instructor-provided, which materially changes how an agent should present and trust the numbers.

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?

Two compact clauses with the core subject front-loaded and zero filler. The backtick-quoted `days` reference is a nice tie-in to the schema, though the sentence is slightly awkward to parse on first read.

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?

With an output schema present, the description needn't enumerate return fields, yet it helpfully characterizes the two payload sections anyway. Annotations cover the safety behavior. The remaining gap is routing guidance against the many sibling tools, which is not covered.

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 0%, so the description must carry the load for the single `days` parameter. It does communicate the forward-looking window ('for the next `days` days'), but it never states the default of 7 or the expected range/format, leaving partial ambiguity.

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 (workload over the next `days` days) and breaks it into two well-named parts, `facts` and `estimates`, which tells an agent exactly what it gets back. It does not, however, distinguish this tool from close siblings like `what_should_i_do_next` or `upcoming_assignments`, which also surface near-term obligations.

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?

There is no when-to-use guidance, no exclusions, and no named alternative. The forward-looking framing implies a planning use case, but the agent must infer that on its own rather than being told when this beats `daily_briefing` or `upcoming_assignments`.

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