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get_run_details

Retrieve comprehensive test execution data including statistics, suites, cases, git metadata, and error details to analyze test health or debug failures in TestDino projects.

Instructions

Get detailed information about test runs. Shows test statistics (passed, failed, skipped, flaky), all test suites and cases, git metadata, and error details. Supports batch operations (comma-separated IDs, max 20). Use this to analyze test execution health or debug specific failures.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
projectIdYesProject ID (Required). The TestDino project identifier.
testrun_idNoTest run ID(s). Single ID or comma-separated for batch (max 20). Example: 'test_run_123' or 'run1,run2,run3'.
counterNoFilter by test run counter (sequential number).
Behavior4/5

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

With no annotations provided, the description carries full burden and does well by disclosing batch operation limits (max 20), the types of information returned (statistics, suites, git metadata, errors), and the tool's purpose for analysis/debugging. It doesn't cover rate limits or authentication needs, but provides solid behavioral context.

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?

Two sentences that are front-loaded with core functionality and usage guidance. Every sentence earns its place: first describes what the tool does, second provides usage context and batch operation details. No wasted words.

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 read operation with no annotations and no output schema, the description provides good context about what information is returned and how to use it. It could be more complete by specifying the return format or pagination, but covers the essential aspects well given the tool's complexity.

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 description coverage is 100%, so the baseline is 3. The description adds value by mentioning batch operations (comma-separated IDs, max 20), which aligns with the 'testrun_id' parameter, but doesn't provide additional semantic context beyond what the schema already documents for parameters.

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 verb ('Get detailed information') and resource ('about test runs'), specifying what information is retrieved (test statistics, test suites/cases, git metadata, error details). It distinguishes from siblings like 'list_testruns' by focusing on detailed analysis rather than listing.

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?

Explicitly states when to use this tool ('to analyze test execution health or debug specific failures') and includes practical guidance on batch operations (comma-separated IDs, max 20). It differentiates from 'list_testruns' by emphasizing detailed analysis over listing.

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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