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get_test_run_summary

Read-only

Fetch aggregated execution summary for a Jira test run/cycle: item counts, status breakdown, execution progress, and pass rate.

Instructions

Aggregated execution summary of a test run / test cycle: composite read-only call of GET /testrun/{key} plus every page of its results (with the flat-endpoint fallback of get_test_run_results). Counts the LAST execution of each item — the run object names them, so latestResults and executed never exceed itemCount — grouping by status name verbatim in byStatus; nothing is normalized. Default statuses: 'Not Executed', 'In Progress', 'Pass', 'Fail', 'Blocked' — case-sensitive internal names; instances may define custom ones. runStatus is the status of the RUN itself (e.g. 'In Progress', 'Done'), not an execution status. executed counts every counted result whose status is not the literal 'Not Executed'. executionProgressPct = executed/itemCount (executed/latestResults when the run exposes no items), so an item with no counted last execution counts as not executed and note says how many there are. passRatePct is the share of the literal status 'Pass' among executed — 0 when nothing passed, and absent only when executed is 0. Returns { key, name, runStatus, itemCount?, latestResults, executed, executionProgressPct?, byStatus, passRatePct?, note? }.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
testRunKeyYesTest run (cycle) key, e.g. PROJ-R123 (PROJ-C123 on older instances)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.5

TDQS

A4.4/5.0
Behavior5/5

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

Annotations only declare readOnlyHint=true; the description carries the rest and does so richly — counting semantics ('LAST execution of each item'), the guarantee that latestResults/executed never exceed itemCount, case-sensitive verbatim status grouping, and edge cases like passRatePct being absent only when executed is 0. This is far beyond what the annotation provides.

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?

Dense and front-loaded: purpose first, then counting rules, then return shape. Every sentence carries semantic weight about the output contract, though the run-on structure and parentheticals make it heavier than strictly necessary.

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?

No output schema exists, so the description must define the return contract — and it does, enumerating every field (key, name, runStatus, itemCount, latestResults, executed, executionProgressPct, byStatus, passRatePct, note) plus the derivation of the computed fields. Nothing needed to interpret the result is missing.

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?

There is a single parameter with 100% schema description coverage, including an example key format (PROJ-R123 / PROJ-C123). The description adds no additional parameter meaning, so the baseline of 3 applies.

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+resource ('aggregated execution summary of a test run / test cycle') and immediately disambiguates it from siblings get_test_run and get_test_run_results by describing it as a composite read that aggregates counts. An agent can tell exactly what this returns versus the raw endpoints.

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?

The description names the underlying endpoint (GET /testrun/{key}) and the fallback path (get_test_run_results), giving the agent context for when this aggregation path applies. It does not, however, explicitly say 'use this instead of get_test_run when you need counts' or state exclusions, so routing is inferred rather than stated.

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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