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lstpsche

@lstpsche/apidog-mcp

by lstpsche

apidog_pipeline

Run a 3-step pipeline to wipe an Apidog module, create cases from structured data, and overlay an OpenAPI spec in batches. Accepts file paths or inline data.

Instructions

Run the proven 3-step pipeline: (1) wipe module, (2) create cases from structured data, (3) overlay enriched OpenAPI spec in batches. Accepts file paths or inline data.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
casesNoStructured endpoint cases to create in step 2
moduleYesModule name
projectNoProject name. Required when multiple projects are configured, optional otherwise.
batchSizeNoPaths per import batch for step 3 (default 15)
openapiSpecNoOpenAPI spec as JSON object
openapiSpecPathNoPath to enriched OpenAPI spec JSON file
Behavior4/5

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

With no annotations, the description carries the burden of behavioral disclosure. It discloses the destructive first step ('wipe module'), batching behavior in step 3, and flexibility in input ('file paths or inline data'). It does not mention irreversibility or permissions, but the key pipeline behavior is transparent.

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 a single, dense sentence that lists the three pipeline steps efficiently. Every word contributes to understanding, and the enumerative structure is easy to parse. No fluff or repetition.

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 complex tool with 6 parameters and no output schema, the description provides crucial context by explaining the order and nature of the steps, which aids understanding why the parameters exist. It does not describe return values or error handling, but the pipeline steps give sufficient high-level completeness for an agent 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?

The schema has 100% parameter descriptions, so the baseline is 3. The description adds a small amount of extra context by mentioning that the pipeline accepts 'file paths or inline data', which maps to openapiSpec vs openapiSpecPath, but it does not elaborate on the parameters beyond what the schema already provides.

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 explicitly states the tool's purpose as a 3-step pipeline with enumerated actions (wipe, create cases, overlay OpenAPI spec), using a specific verb 'Run' and resource 'pipeline'. It clearly differentiates from sibling tools by combining their individual functions into one composite operation.

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 through the pipeline steps, indicating when to use it (when a full setup is required) but does not explicitly contrast with alternatives like running the individual tools (apidog_wipe, apidog_create_cases, apidog_import_openapi) separately. There is no 'when not to use' guidance, but the context is reasonably clear.

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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