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Get Test Run Results

get_test_run_results

Fetches test cases in a Tuskr test run with their latest results, letting you filter by status such as FAILED to identify cases needing re-checking after a fix.

Instructions

Fetches the test cases in a test run together with their latest result.

The main use is confirmation testing: pass status='FAILED' to get back only the test cases that need re-checking after a fix.

Input Schema

NameRequiredDescriptionDefault
pageNopage number to fetch, 100 records per page. Default is 1. Ignored when fetch_all_pages is True.
statusNoa result status key, or a list of them, e.g. 'FAILED' or ['RETEST', 'FAILED']. Only test cases whose current status is one of these are returned. Status keys are configured per tenant, so use the keys defined in your own Tuskr account.
test_runYesID of the test run. Tuskr addresses the run in the URL path for this endpoint, so unlike the other tools a run name is not accepted here.
test_casesNoa test case ID, key or name, or a list of them. Only the matching test cases are returned.
trim_responseNoif True (default), each row's nested testCase object is reduced to id, key, name and testRunTestCases (this run's own result and its linked issue keys). The full object also carries the case's entire resultHistory and every issue key ever linked to it, which can push a busy run past the MCP transport size limit. Set it to False when that history is genuinely needed.
fetch_all_pagesNoif True, walks every page and returns the combined rows. Tuskr rate-limits every plan at 10 requests/second, so prefer a status or test_cases filter over fetching everything.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.1.5

TDQS

A3.7/5.0
Behavior3/5

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

No annotations are present, so the description carries the full behavioral burden. 'Fetches' implies a read, and the confirmation-testing framing is genuinely useful, but it says nothing about pagination (100 records/page, fetch_all_pages), the 10 req/s rate limit, or the default response trimming — all disclosed only in the schema text.

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 short sentences, purpose first and the most actionable hint second. Every sentence earns its place and nothing is buried.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a six-parameter retrieval tool with no output schema and no annotations, the description covers what it returns at a high level but omits paging behavior, response shape trimming, and rate-limit pressure — all left to the schema. Adequate, not self-sufficient.

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 schema already defines status, trim_response, page, and fetch_all_pages in detail. The description adds usage-level meaning for status ('pass FAILED to get only cases needing re-checking') but no format or syntax beyond the schema baseline.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource: fetches the test cases in a test run alongside their latest result. That is clearly distinct from siblings like add_test_run_results or get_test_run_timeline, though it never explicitly differentiates itself from get_test_run_details, which an agent could plausibly confuse it with.

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?

Gives a concrete usage scenario (confirmation testing after a fix) and the exact call pattern that serves it (status='FAILED'). It stops short of naming alternatives or stating when not to use it, so it is clear context without exclusions.

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