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List Test Suites

list_test_suites

Retrieve a project's test suites with their embedded sections to discover suite and section IDs for filtering test cases. Returns one page of raw rows, count and meta; it does not fetch further pages.

Instructions

Retrieves list of test suites and their associated sections in a project.

Use this to discover suite and section IDs. Pass them to list_test_cases as filter_test_suite and filter_test_suite_section instead of reading the IDs off existing test case rows.

Each suite row embeds its sections. Returns Tuskr's raw rows, count and meta for a single page; this tool does not fetch further pages.

Input Schema

NameRequiredDescriptionDefault
pageNocontrols number of records in output, every page contains 100 records. Default is 1.
filter_nameNoto filter test suites with name containing the specified value
filter_projectYesspecifies the project ID to list the test suites of. Required.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.1.5

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations, the description carries the burden and does well: it discloses the result shape ('raw rows, count and meta'), the nesting behavior ('Each suite row embeds its sections'), and the pagination limit ('does not fetch further pages'), which is the non-obvious failure mode. It stops short of stating read-only safety, auth requirements, or whether the rows are raw/untransformed in a way that matters for parsing.

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 paragraphs, each front-loaded with its most important claim: what it returns, why to call it, then the pagination caveat. No filler sentences and the limiting constraint comes last where it is easy to catch.

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 3-parameter read tool with no output schema and no annotations, the description covers purpose, downstream use, return shape, and pagination adequately. It leaves minor ambiguity about whether 'count' is a page count or total, and whether sections themselves can be filtered.

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 coverage is 100%, so page and filter_project are already fully documented in the schema. The description adds no syntax or formatting detail for filter_name or page beyond pointing at the IDs the results yield. Baseline 3 is appropriate when the schema does the heavy lifting.

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?

States a specific verb and resource ('Retrieves list of test suites and their associated sections') with an explicit scope ('in a project'). The following sentence distinguishes it from the sibling list_test_cases by naming it and describing the different job each 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?

Gives a concrete when-to-use ('discover suite and section IDs') and a concrete what-to-do-next ('Pass them to list_test_cases as filter_test_suite and filter_test_suite_section'). It even states an anti-pattern to avoid ('instead of reading the IDs off existing test case rows'), which is exactly the routing guidance an agent needs.

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