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england-works-watch

list_supported_change_events

Read-onlyIdempotent

Free supported-event list. Use when asking which sponsor events the tool can handle, which change types/categories are supported, or to list supported events: absence, salary, role, work location, start delay, stop sponsorship, organisation change, TUPE, merger, takeover. Capability/list only; not impact, reporting, or required-action decisions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the tool's safety profile is covered. The description adds useful behavioral context by clarifying this is a pure capability/list endpoint and not an analysis or action-oriented tool. It does not contradict the annotations and adds value beyond them.

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 compact, front-loading the core purpose and usage conditions, and then listing example events. The phrase 'Free supported-event list' is slightly ambiguous because 'free' could mean cost-free or free-of-analysis, but the remainder of the sentence clarifies meaning. Overall, every sentence earns its place and there is no padding.

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 zero-parameter, read-only list tool with an output schema, the description is complete. It states what the tool returns, when to use it, and what it will not do. Sibling tool differentiation is handled well. The agent has everything needed to select and invoke this tool correctly.

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?

The tool has zero parameters, so schema coverage is trivially 100% and no parameter documentation is needed. The description appropriately focuses on what the returned list contains rather than on input semantics. The baseline of 4 for zero-parameter tools is appropriate here.

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?

The description clearly identifies the tool as a list operation for supported change events, enumerating specific event types (absence, salary, role, work location, etc.). It also distinguishes itself from analysis-oriented siblings by explicitly saying it is 'capability/list only; not impact, reporting, or required-action decisions.' This leaves no ambiguity about what the tool does.

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?

The description explicitly states when to use the tool: when asking which sponsor events the tool can handle, which change types/categories are supported, or to list supported events. It also provides clear exclusions, directing users away from impact, reporting, or required-action decisions. This effectively guides the agent away from sibling tools like assess_change_impact or batch_assess_changes.

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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