PM-Skills MCP

pm_validate

Check if a product management artifact matches the required sections of a skill template, returning a section checklist and improvement suggestions.

Instructions

Validate a PM artifact against its skill template.

Checks that an output document contains the expected sections from a skill's template.

Args:

skill (string, required): The skill name to validate against (e.g., "prd", "hypothesis", "user_stories")
output (string, required): The artifact content to validate

Returns: Validation result with section checklist and suggestions for improvement.

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": {
      "skill": "<skill>",
      "output": "<output>"
    },
    "name": "pm_validate"
  }
}

Input Schema

Name	Required	Description	Default
`skill`	Yes	Skill name to validate against (e.g., "prd", "hypothesis")
`output`	Yes	The artifact content to validate

Schema Changelog

Changes observed during successful MCP inspections.

First observedv2.9.3Jul 29, 2026

TDQS

A3.8/5.0

Behavior4/5

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

The description implicitly indicates this is a read-only validation operation by stating it returns a result. Without annotations, it carries the behavioral transparency burden well, though it could be more explicit about having no side effects.

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?

The description is well-structured with a clear purpose sentence, followed by parameter and return value descriptions. It is concise without extraneous information, though the parameter section is somewhat redundant with the schema.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple tool with two parameters and no output schema, the description fully covers what the tool does, its inputs, and its output format. No additional information is needed for correct usage.

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% with clear descriptions for both parameters. The tool description adds minimal additional meaning beyond repeating parameter purposes, meeting 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 tool validates a PM artifact against its skill template, specifying the verb and resource. It distinguishes from sibling tools like pm_list_skills and pm_search_skills, which have different purposes.

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 guidance is provided on when to use this tool versus alternatives, such as when to validate versus simply listing or searching skills. The description lacks explicit usage context or exclusions.

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