PMFlow MCP

generate_prd

Generates a structured, production-ready PRD with requirements, tech stack, constraints, and success metrics from your product title, problem, audience, and key features.

Instructions

Generates a structured, production-ready PRD with requirements, tech stack, constraints, and success metrics.

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": {
      "title": "<title>",
      "problem_statement": "<problem_statement>",
      "target_audience": "<target_audience>",
      "key_features": "<key_features>"
    },
    "name": "generate_prd"
  }
}

Input Schema

Name	Required	Description
`title`	Yes	Title of the product or feature
`key_features`	Yes	List of core features
`success_metrics`	No	Optional measurable KPIs
`target_audience`	Yes	Target personas and user profiles
`technical_stack`	No	Optional list of technologies
`problem_statement`	Yes	Core problem being solved

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Oct 21, 2026

TDQS

C2.9/5.0

Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden. It discloses what the artifact contains but not whether generation is deterministic or LLM-backed, whether the PRD is persisted or merely returned, or what the caller should do with it next — meaningful gaps for a generation tool.

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?

A single tight sentence with the outcome front-loaded; no filler or restatement of the tool name. Slightly dense with the enumerated contents, but every clause is informative.

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?

With no annotations and no output schema, the description should at minimum say what form the generated PRD takes and how it feeds the sibling tools. It conveys the artifact's sections but leaves the return value and downstream workflow unstated — adequate but with clear gaps.

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 coverage is 100%, so all six parameters are already documented. The description's list of contents loosely maps to key_features, technical_stack, and success_metrics, but it introduces 'constraints', which is not an input parameter, and adds no input-formatting detail beyond the schema. Baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb (Generates) and resource (PRD), and enumerates the artifact's contents: requirements, tech stack, constraints, success metrics. Clear on its own, but it never distinguishes itself from siblings like decompose_stories or export_markdown_specs, which operate on the same PRD artifact.

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

Usage Guidelines2/5

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

No when-to-use guidance, no prerequisites, and no mention of the other tools in the workflow. An agent must infer from the name alone that this is the first step before decompose_stories, validate_acceptance_criteria, or export_markdown_specs.

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

Deploy Server