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Run Bruno filter scenarios

run-filter-scenarios

Runs temporary Bruno request variants with chosen disabled query params enabled and validates HTTP status and response payload consistency; baseline calls separate ignored filters from zero matches.

Instructions

Run temporary Bruno request variants with selected disabled query params enabled, then validate HTTP status and response payload consistency. Each request is also run once without filters (baseline) to distinguish an ignored filter (response identical to baseline) from a filter that legitimately returns zero matches. Infrastructure failures (auth, routing, timeout, connectivity) are reported as inconclusive, never as filter defects. Source collection files are not modified.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
scenariosNoOptional explicit filter scenarios. When omitted, scenarios are generated from disabled query params.
variablesNoOptional non-secret KEY=value variables.
collectionYesPath to the Bruno collection directory or opencollection.yml file.
environmentNoOptional Bruno environment name.
max_scenariosNoMaximum number of generated scenarios when scenarios are omitted.
inherited_variablesNoOptional secret variable names to inherit from the MCP server process.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.1

TDQS

A4.2/5.0
Behavior4/5

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

No annotations are provided, so the description carries the full burden, and it does well: it discloses that each request also runs a baseline, that infrastructure failures are reported as inconclusive rather than defects, and that source collection files are not modified. Missing details on auth requirements and whether requests hit live endpoints (side effects) keep it from a 5.

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?

Four tight sentences, front-loaded with the core action and followed by the baseline rationale, failure semantics, and the non-mutation guarantee. No filler.

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?

With no output schema, the description could say more about the shape of the returned results (per-scenario status, baseline comparison fields), but it covers the key behavioral and side-effect questions an agent needs before invoking a multi-request execution tool.

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 documents every parameter; baseline is 3. The description adds conceptual context about disabled query params and baseline runs but no syntax or formatting detail beyond the schema.

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 and resource ('Run temporary Bruno request variants with selected disabled query params enabled') plus the validation goal, which cleanly separates it from siblings like run-collection and run-full-validation. An agent can tell this is the filter-scenario verifier without opening the schema.

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 sets up the use case clearly: run filter variants to distinguish an ignored filter (identical to baseline) from one that legitimately returns zero matches. It does not explicitly say when NOT to use this or name run-collection/run-full-validation as alternatives, but the context is unambiguous.

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