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QMetry: Fetch QMetry Project Info

qmetry_fetch_qmetry_project_info
Read-onlyIdempotent

Retrieve QMetry project configuration, including viewId and folderPath, to enable test case operations. Use it to get necessary identifiers before fetching test cases.

Instructions

Fetch QMetry project information including viewId and folderPath needed for other operations

Toolset: Projects

Parameters:

  • projectKey (string): Project key - unique identifier for the project (default: "default")

Output Description: JSON object containing project details, viewIds, folderPaths, project configuration, 'dateTimeFormatID' (active date format ID), and 'dateTimeFormatNew' array (each entry: { id, name, unique_value } — use unique_value of the matching entry as the date format pattern for all API date fields).

Use Cases: 1. Get project configuration before fetching test cases 2. Retrieve available viewIds for test case listing 3. Get folderPath information for project navigation 4. Validate project access and permissions

Examples:

  1. Get default project info

{}

Expected Output: Project configuration with viewIds, folderPaths, and project details

  1. Get specific project info

{
  "projectKey": "MAC"
}

Expected Output: MAC project configuration with available views and folders

Hints: 1. Always call this first when user doesn't provide viewId or folderPath 2. Use 'default' project key when user doesn't specify one 3. Extract viewId from latestViews.TC.viewId for test case operations 4. Use empty string '' as folderPath for root directory 5. DATE FORMAT — IMPORTANT: response contains 'dateTimeFormatID' (number) and 'dateTimeFormatNew' (array). 6. dateTimeFormatID = active format ID for this project. 7. dateTimeFormatNew = [{ id, name, unique_value }] — find entry where id === dateTimeFormatID. 8. unique_value is the authoritative date format pattern using Java/QMetry conventions: 9. yyyy = 4-digit year | MM = 2-digit month (01-12) | dd = 2-digit day | MMM = 3-letter month (Jan/Feb/...) 10. Example mappings: 11. unique_value 'MM-dd-yyyy' → format: 12-25-2024 12. unique_value 'dd-MM-yyyy' → format: 25-12-2024 13. unique_value 'yyyy-MM-dd' → format: 2024-12-25 14. unique_value 'dd-MMM-yyyy' → format: 25-Dec-2024 15. Always use this format when sending date values in any create/update payload. 16. Always parse user-provided dates and reformat them to this pattern before sending to API.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
projectKeyNoProject key - unique identifier for the projectdefault
Install Server

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already indicate readOnly, idempotent, and non-destructive. The description adds substantial behavioral context by detailing the response structure (viewIds, folderPaths, dateTimeFormatID/New), explaining how to extract viewId from latestViews.TC.viewId, and providing an exhaustive date format mapping that is critical for downstream API calls.

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 well-structured with clear sections (Toolset, Parameters, Output, Use Cases, Examples, Hints). It is lengthy, especially the date format hints, but that detail is necessary and each section serves a purpose. Slight redundancy in the numbered hints keeps it from a 5.

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?

With no output schema, the description takes on the full burden of explaining return values. It thoroughly covers the response fields, provides two examples with expected outputs, and includes critical date format instructions. It is complete for an agent to know when to call and how to interpret results.

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?

Schema coverage is 100% and includes a description and default for projectKey. The description adds value with examples, clarification that 'default' is used when unspecified, and context that folderPath for root is an empty string (though that's not a direct parameter). It goes beyond the schema but is not exceptionally rich.

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 it fetches QMetry project information including viewId and folderPath, and explicitly notes this is needed for other operations. This distinguishes it from sibling tools like qmetry_fetch_qmetry_list_projects and qmetry_set_qmetry_project_info.

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?

Provides explicit use cases and the hint 'Always call this first when user doesn't provide viewId or folderPath', giving clear when-to-use guidance. However, it doesn't explicitly contrast with alternative tools (e.g., list projects, set project info), so it lacks full when-not-to-use exclusions.

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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