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Stride — AI software delivery platform

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Generate process

stride.generate_process

Generate a BPMN business process for a story from its title + description + acceptance criteria. Models the flow (start, tasks, decisions, end), validates it with bpmnlint, and persists a draft process in the Optimize module linked to the story. Identify the story by ticket key (e.g. "ORB-526") or UUID. Optionally pass detail ("happy" | "full") and free-text guidance. Can take up to ~4 minutes, longer than many MCP clients wait. If it is still running after about 52 seconds this tool answers "still running" with a toolCallId and finishes in the background, saving the result when done. Meanwhile a repeat call for the same story (for a refine, the same option) starts nothing and answers "still running" again; stride.get_tool_call_status follows the run: given that toolCallId and waitSeconds 40 it waits for the run (a 3-minute run takes about 5 calls) and returns the result once it is saved, or says it failed. Cancelling the call before it answers stops the run and saves nothing.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "storyId": "<storyId>"
    },
    "name": "stride.generate_process"
  }
}

Input Schema

NameRequiredDescriptionDefault
detailNo"happy" (core path, default) or "full" (include exception paths).
storyIdYesStory ticket key like "ORB-526" (preferred) or a Stride UUID.
instructionsNoOptional extra guidance (e.g. "model the refund branch").

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior5/5

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

Extremely explicit about behavior beyond annotations: ~4 minute runtime, the 52-second 'still running' + toolCallId pattern, background completion, deduplication of repeat calls for the same story/option, and that cancelling saves nothing. This directly informs the agent's retry/poll strategy, which annotations alone (openWorldHint, non-idempotent) could not convey.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Core purpose is front-loaded in the first clause, followed by the long-running/polling mechanics. The later sentences are long and compound (several clauses about repeat calls, waiting, and cancellation), but each carries non-redundant operational information.

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?

Given no output schema, the description does explain the intermediate return ('still running' + toolCallId) and that the final result is saved, plus the how-to-follow-up path via stride.get_tool_call_status. It stops short of describing the shape of the final saved-process result, a minor remaining gap.

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% and already documents all three parameters including the detail enum. The description mostly restates those semantics (ticket key example, detail options) without adding format or constraint details beyond the schema, so baseline 3 applies.

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 artifact: generates a BPMN process from a story's title/description/acceptance criteria, validates with bpmnlint, and persists a draft linked to the story. This clearly separates it from siblings like generate_diagram, get_process, or list_processes.

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?

Gives the input precondition (story identified by ticket key or UUID) and optional detail/guidance knobs. It does not explicitly contrast with generate_diagram or explain when to regenerate vs. refine an existing process, but the usage context is 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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