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product-on-purpose

PM-Skills MCP

pm_workflow_customer_discovery

Transforms raw research into a validated problem worth solving. Guides through interview synthesis, JTBD canvas, opportunity tree, and problem statement.

Instructions

Customer Discovery workflow - Transform raw research into a clear, validated problem worth solving.

Effort Level: standard

Steps:

  1. pm_interview_synthesis

  2. pm_jtbd_canvas

  3. pm_opportunity_tree

  4. pm_problem_statement

Use this tool to get a complete workflow plan. The AI client orchestrates execution by calling each step's tool in sequence.

Args:

  • topic (string, required): The subject or feature for this workflow

  • context (string, optional): Additional context for the workflow

Returns: Markdown workflow plan with steps, guidance, and execution instructions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topicYesThe subject or feature for this workflow
contextNoAdditional context, constraints, or requirements
Behavior2/5

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

No annotations are provided, so the description must carry the full burden. It mentions 'Effort Level: standard' and describes the output format, but does not disclose side effects, idempotency, rate limits, or error conditions, leaving significant behavioral aspects unaddressed.

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, effort level, steps list, and usage instruction. It is slightly verbose but every section adds value, earning a high score for conciseness and front-loading.

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?

The tool returns a workflow plan, and the description covers input parameters, steps, and execution instructions. It lacks details on interpreting the plan or error handling, but given the absence of an output schema, the description is fairly complete for its purpose.

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 both parameters already described. The description repeats the schema ('topic (string, required)', 'context (string, optional)') without adding new semantics, achieving a baseline score of 3.

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's purpose: 'Customer Discovery workflow - Transform raw research into a clear, validated problem worth solving.' It lists the specific steps and differentiates from sibling workflows like pm_workflow_feature_kickoff by its unique name and step sequence.

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 includes 'Use this tool to get a complete workflow plan' which indicates a clear context for use. However, it lacks explicit guidance on when not to use it or alternatives among the many sibling workflows, leaving differentiation largely implicit.

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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