Starts a blueprint workflow that converts an idea or PRD into requirements, component selections, architecture, and review; returns a task ID for status polling.
启动真实正向蓝图流程：点子/PRD → 需求拆解、五要素、组件选型、架构设计、审稿。返回任务 ID，需轮询 status。使用已登录 ChatGPT 账号调用云端模型。
| Name | Required | Description | Default |
|---|---|---|---|
| idea | No | 用户的点子或完整 PRD 文本 | |
| prd_path | No | 可选 UTF-8 PRD 文件绝对路径 | |
| max_calls | No | ||
| max_tokens | No |
Changes observed during successful MCP inspections.
v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations only give the generic readOnly=false/destructive=false/openWorld=true profile. The description adds genuinely useful behavior beyond that: the call is asynchronous and returns a task ID requiring polling, and it depends on a logged-in ChatGPT account hitting a cloud model (external auth/dependency, consistent with openWorldHint). It does not say what artifacts get committed or whether a run can be undone.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two dense sentences: purpose and pipeline first, then the operational outcome (task ID + polling) and the auth condition. No filler or repetition of the tool name.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
It covers the async lifecycle and auth context, which is the most important missing piece given no output schema. However, with zero required parameters it never clarifies that at least one of idea/prd_path must be supplied, nor how the budget parameters constrain the run — a real gap for a 4-parameter launch tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 50% (idea and prd_path documented, max_calls and max_tokens bare). The description echoes the 点子/PRD inputs but adds no format, precedence (idea vs prd_path), or meaning for the budget parameters. Baseline 3 for partial coverage with only marginal added value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb (启动/start) and resource (真实正向蓝图流程) and enumerates the pipeline it drives (需求拆解、五要素、组件选型、架构设计、审稿), which clearly separates it from siblings like status/result/cancel. It also names the async handoff (returns task ID, poll status), so an agent can place it in the lifecycle.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage is implied rather than stated: this is the entry point to the blueprint flow and it hints that status polling follows. There is no explicit 'use this instead of blueprint_resume when…' or any exclusion rule, so the agent must infer when to start fresh versus resume an existing task.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.