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eyaushev

Swagger Testcase MCP

export_test_cases

Export generated API test cases from Swagger/OpenAPI specifications to multiple formats including Postman, TestRail, pytest, and CSV for testing and documentation purposes.

Instructions

Export previously generated test cases in various formats: markdown, json, csv, allure_csv, gherkin, postman, k6, pytest, testrail_csv (Steps template), testrail_csv_text (Text template).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
endpointYesEndpoint key like "POST /api/orders", or "_last_batch" for the last batch generation
formatYesExport format. testrail_csv uses Steps template (one row per step), testrail_csv_text uses Text template (all steps in one field)
output_pathNoCustom file path to save the export. If omitted, saves automatically to the working directory with a generated filename.
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions export formats and file saving behavior, but lacks critical details like whether this operation requires specific permissions, if it's idempotent, what happens on failure, or if there are rate limits. For a tool that presumably writes files, this leaves significant behavioral gaps.

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 efficiently structured as a single sentence that front-loads the core purpose and follows with a comprehensive list of supported formats. Every element serves a clear purpose with zero wasted words, making it easy to parse while being information-dense.

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?

Given the tool's moderate complexity (3 parameters, file output operation) and lack of both annotations and output schema, the description is incomplete. It covers what formats are available but doesn't address error conditions, output structure, or operational constraints that would help an agent use it correctly in various scenarios.

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 all three parameters thoroughly. The description adds minimal value beyond the schema by listing format options, but doesn't provide additional context about parameter interactions, default behaviors, or practical examples. This meets the baseline for high schema coverage.

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 clearly states the specific action ('Export') and resource ('previously generated test cases'), and distinguishes this tool from siblings like 'generate_test_cases' or 'generate_test_cases_batch' by focusing on exporting existing content rather than creating new content. The verb+resource combination is precise and unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage context by specifying 'previously generated test cases,' suggesting this tool should be used after test generation. However, it doesn't explicitly state when to use this versus alternatives like 'analyze_endpoint' or 'validate_spec,' nor does it provide exclusion criteria or prerequisites for successful export operations.

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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