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run_folder
Destructive

Runs every saved request in a folder or workspace in order, with scripts and assertions, to verify an API still works after a change. Filter by tags, repeat with data, and get counts plus failed checks.

Instructions

Send every request in a folder, or in the whole workspace, in order, with scripts and assertions, the way the collection runner does. tags and exclude_tags narrow the run to a subset such as smoke tests; data and iterations repeat it. Use it to check that an API still works after a change. Returns the counts and, for failed requests only, the error, the failed checks (failedTests) and the console output.

Input Schema

NameRequiredDescriptionDefault
bailNoStop at the first failing request.
dataNoRun once per item; each item's fields become variables for that iteration, such as [{"userId": 1}, {"userId": 2}], and win over the environment and a request's own vars.
tagsNoRun only requests with at least one of these tags, as list_requests shows them. Case does not matter.
folderNoThe folder to run, by name or path. Leave out to run every request in the workspace.
iterationsNoRepeat the run this many times, or use only the first rows of data.
exclude_tagsNoSkip requests with any of these tags.

Output Schema

NameRequiredDescriptionDefault
hintNo
summaryNo
failuresNo
withheldNo
durationMsNo
iterationsNo
unresolvedNo
environmentNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.7.19

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already disclose destructiveHint=true, openWorldHint=true, readOnlyHint=false and idempotentHint=false, so the safety profile is covered. The description adds beyond that by explaining ordered execution of every request, scripts and assertions, tag-based subsetting, iteration behavior, and failed-request return details. It does not add auth, rate-limit, or side-effect specifics, but the annotations carry the main risk signal.

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?

The description is front-loaded with the core action and scope, then adds parameter behavior, a use case, and return details in three efficient sentences. Each sentence contributes useful information, and there is no boilerplate or repetition.

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?

Given six optional parameters, full schema description coverage, rich annotations, and an output schema, the description is complete enough to call the tool correctly. It covers folder versus workspace scope, tag filtering, data/iteration repetition, intended use, and return shape without over-explaining schema-covered details.

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 description coverage is 100%, so the baseline is already a 3. The description adds useful semantics beyond the schema by explaining that tags and exclude_tags narrow the run to subsets such as smoke tests and that data and iterations repeat the run. It omits bail, but the schema fully documents that parameter.

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 states a specific verb and resource: sending every request in a folder or the whole workspace in order, with scripts and assertions. It clearly distinguishes this batch collection-runner behavior from single-request siblings through the folder/workspace scope and execution order. The 'check that an API still works after a change' framing also separates it from load-focused tools.

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 gives a clear usage context: checking that an API still works after a change, and narrowing runs to smoke tests with tags. It does not explicitly state when not to use this tool or name alternatives like send_request for a single request. This matches a clear-context-but-no-exclusions rating.

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