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Smart Browser MCP

api_test_suite

Execute a set of API test cases sequentially and receive an aggregated pass/fail report. Optionally save the case list for later replay.

Instructions

Run a list of API test cases (same shape as api_assert's inputs) in sequence and return an aggregated pass/fail report. Pass save=true with a name to persist the case list to disk for later replay via api_suite_run.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNo
saveNo
casesYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.1

TDQS

A4/5.0
Behavior3/5

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

With no annotations, the description carries the behavioral disclosure burden. It does reveal that cases run in sequence, produce a pass/fail report, and can be persisted with save=true. However, it leaves out HTTP side effects, required environment state, and behavior when an individual case fails.

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 concise sentences with no filler. The primary action, output format, and persistence option are all presented clearly and in order of importance.

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 tool with only three parameters and no output schema, the description covers the essential call pattern, persistence route, and sibling-tool relationship. Minor gaps around the exact report shape and failure semantics keep it from a perfect score, but an agent can understand how to invoke it correctly.

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 0%, so the description must provide the parameter meaning. It explains cases as 'same shape as api_assert's inputs' and describes the save/name interaction. It does not clarify whether name is always required or only when saving, and individual case fields are left to 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?

The description opens with a specific action and object: 'Run a list of API test cases' and immediately states the output is an aggregated pass/fail report. It also differentiates from siblings by referencing api_assert's input shape and the save/replay relationship with api_suite_run.

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 makes it clear this is for executing a batch of cases, while the api_assert reference implies single-assertion alternatives. It explicitly explains the persistence workflow via save=true and name, and points to api_suite_run for replay. It lacks explicit 'when not to use' statements, but the context is sufficient.

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