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List Test Schedules

list_test_schedules
Read-only

List the schedules of a test suite with their cron expression, timezone and next run time. Pass scheduleId to get one schedule instead — testSuiteId is then not needed. Requires project context.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
skipNoNumber of schedules to skip (for pagination, default 0)
takeNoNumber of schedules to return (default 100, max 100)
scheduleIdNoPublic Id (Guid) of a single schedule. When given, returns only that schedule.
testSuiteIdNoPublic Id (Guid) of the test suite. Required unless scheduleId is given.

Schema Changelog

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

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

The readOnlyHint annotation already indicates a safe read operation, and the description adds the practical context that project context is required. It does not overpromise side effects or hide behavior, so transparency is strong.

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?

The description is concise and well-structured, with the main purpose stated first and parameter guidance following naturally. Every sentence adds useful information without redundancy.

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?

The description is complete for the tool's complexity: it covers what is listed, the key output fields, the parameter selection rule, and the project context prerequisite. No output schema is present, but the description sufficiently conveys the expected result shape.

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

Parameters5/5

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

Although the schema already covers all parameters, the description adds important relational meaning: testSuiteId is required unless scheduleId is given, and scheduleId returns only that schedule. This goes beyond the raw schema and helps the agent choose the correct parameter combination.

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 states the tool lists schedules for a test suite and includes the key returned fields (cron expression, timezone, next run time). It also distinguishes the single-schedule variant via scheduleId, which is specific enough to avoid confusion with sibling tools.

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

Usage Guidelines3/5

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

The description gives useful guidance about using scheduleId instead of testSuiteId and notes the project context requirement. However, it does not explicitly compare this tool to related alternatives such as get_scheduled_publishes or list_test_suites, so when-to-use guidance is only partially provided.

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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TDQS

A3.9/5.0
Disambiguation4/5

The tools are mostly distinct with clear descriptions. Some pairs like get_header_policies vs get_resolved_headers or get_environment_verification vs get_monitoring_sync_status could be slightly confusing, but the descriptions clarify scope and purpose.

Naming Consistency5/5

All tools follow a consistent snake_case verb_noun pattern (get_, list_, create_, update_, manage_, etc.). Even the few bare verbs like 'search' and 'set_context' are consistent with the naming scheme.

Tool Count1/5

With 165 tools, the server is extremely heavy. This far exceeds the 'too many' threshold of 25+, making it difficult for an agent to navigate and select the right tool efficiently.

Completeness5/5

The tool surface covers a very broad API lifecycle domain: specs, environments, test cases, monitors, mock servers, security, governance, documentation, and team management. Read and write operations are present across most areas, with no obvious missing core functionality.

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