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moodle-watch

moodle-watch

by Valej18
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

set_course_policy

Determine whether a course should be watched by setting its state to watch, ignore, or pending, and resolve pending courses with a durable policy decision.

Instructions

Decide whether a course is watched. Use this to answer a pending course.

state is watch, ignore or pending. A decision made with a by other than policy is never overwritten by a policy rule afterwards, so the user's answer sticks.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "course_id": "<course_id>",
      "state": "<state>",
      "by": "<by>"
    },
    "name": "set_course_policy"
  }
}

Input Schema

NameRequiredDescriptionDefault
byYes
stateYes
reasonNo
course_idYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.8/5.0
Behavior3/5

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

No annotations are provided, so the description must carry behavioral disclosure. It does reveal a meaningful rule: decisions made with a 'by' other than 'policy' are never overwritten by a policy rule. However, it does not discuss side effects, response behavior, or whether an existing non-policy decision can be changed directly.

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?

Three short sentences, front-loaded with purpose, then concrete parameter semantics and an important behavioral caveat. Every sentence earns its place with no filler.

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?

For a 4-parameter mutation tool with no annotations and no enums, the description covers the usage trigger, state values, and the key overwrite rule. The optional reason parameter is not explained, but the required parameters are substantially addressed and an output schema exists, making it mostly complete.

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?

The description adds real meaning by enumerating state values (watch, ignore, pending) and explaining the effect of 'by' versus 'policy'. Since schema description coverage is 0%, this helps, but course_id and especially the optional reason parameter receive no semantic explanation.

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 concrete action ('Decide whether a course is watched') and a target resource, and adds 'Use this to answer a pending course' to clarify intent. It does not explicitly contrast with sibling tools like mark_handled, so it stops short of full differentiation.

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 a clear trigger: use this tool when there is a pending course to answer. It does not name alternatives or exclusions, but the usage context is explicit enough for an agent to select the tool.

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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