Product Manager Skills

The Finance Suite is a collection of 7 specialized skills designed for Product Managers to understand, calculate, and apply SaaS finance metrics. It is organized into three functional layers:

1. Foundation Layer: Deep metric understanding and calculation (Skills #1-3).
2. Decision Layer: Interactive advisors for applying metrics to specific PM decisions like features, channels, and pricing (Skills #4-6).
3. Diagnostic Layer: Holistic business health assessment (Skill #7).

The suite covers 32 SaaS finance metrics across revenue, growth, unit economics, and capital efficiency.

The product-manager-skills library provides 70 battle-tested PM frameworks and 6 command workflows designed for use with AI agents (such as Claude Code, Cursor, Codex, n8n, and OpenClaw) and human Product Managers.

Instead of generic AI outputs, this library provides structured knowledge, including the reasoning behind frameworks and failure modes to avoid. It is designed to be used by any agent capable of reading structured knowledge to ensure professional-grade PM deliverables.

The Market Intelligence Suite is a collection of skills designed for market and competitive analysis. It includes a chain of interconnected skills where the output of one serves as the input for the next:

• market-landscape-scan: Initial landscape scan.
• competitive-research-snapshot: Consumes the scan output to create a snapshot.
• competitive-intel-watch: Diffs the snapshot to identify changes.
• battle-card-builder: Rebuilds a battle card based on updates from the watch skill.

Other key entry points include:

• intel-discipline-advisor: An interactive triage card to determine which intelligence discipline to use.
• competitive-analysis-process: An umbrella workflow for orchestrating multiple skills.
• tam-sam-som-calculator: Used in autonomous research modes.

Working capital is the cash required to fund day-to-day operations, representing the gap between paying expenses and collecting revenue.

PM Lever: Changing billing cycles can impact working capital. For example, billing customers annually upfront (instead of monthly) improves working capital by collecting cash sooner, which can then be used to fund growth.

As of v0.4, the project uses a standardized facilitation protocol to ensure consistent behavior in guided skills. This protocol prevents 'facilitation drift' (where interactions become too brief or abrupt) by enforcing a structured, one-question-at-a-time flow.

Key features of the protocol include:

• Session Heads-up: A notification before the session starts.
• Entry Modes: Support for Guided, Context dump, and Best guess modes.
• Progress Labels: Clear indicators of current progress.
• Interruption Handling: Support for pausing and resuming sessions.
• Decision Points: Recommendations provided with numbered choices for clear decision-making.

The canvas is partitioned into three distinct phases to ensure a comprehensive exploration of the problem space:

1. Look Inward: Examine your own assumptions, biases, and how you might be part of the problem (symptoms, why it hasn't been solved, and internal biases).
2. Look Outward: Understand who experiences the problem, who benefits from it, and who has been left out (stakeholders, consequences, and equity).
3. Reframe: Synthesize insights into a clear, actionable problem statement and a "How Might We" question.

Note: This is a problem-framing tool, not a solution brainstorm or a feature request list.

A User Story Map (based on Jeff Patton) organizes work across two dimensions:

• Horizontal axis (Left to Right): The Backbone. Activities arranged in narrative/workflow order (the sequence used to explain the system).
• Vertical axis (Top to Bottom): Priority. The most essential tasks within each activity are placed at the top.

Core Components

• Backbone: Essential activities forming the structural core/narrative flow.
• Walking Skeleton: The highest-priority tasks across all activities, representing the smallest end-to-end functionality (MVP).
• Ribs: Supporting tasks descending vertically under each activity.

Key Strategy

Left-to-Right, Top-to-Bottom Build Strategy: Build incrementally across all major features (horizontal slices) rather than completing one feature fully before starting another.

The autonomous-investigation protocol is a sibling to the workshop-facilitation protocol. The distinction is based on context ownership:

• Autonomous Investigation: The agent holds the context and performs the work.
• Workshop Facilitation: The user holds the context and the agent facilitates the process.

Skills are organized into three hierarchical tiers:

1. WORKFLOW SKILLS (19): Complete end-to-end PM processes (e.g., running a full discovery cycle or writing a PRD).
2. INTERACTIVE SKILLS (27): Guided discovery using an Adaptive Decision Ladder. These skills ask 3-5 targeted questions about your context and provide numbered recommendations.
3. COMPONENT SKILLS (24): Templates for specific deliverables (e.g., writing a user story with acceptance criteria).

Workflow skills orchestrate Interactive skills, which in turn use Component skills.

The v0.80 release, titled AI Product Builder Track, is designed to help product managers use AI to accelerate execution without sacrificing product judgment. The core philosophy is: "Build faster without outsourcing judgment."

Instead of focusing on pure code generation (vibe-coding), this track focuses on the strategic application of AI, including:

• Deciding if a problem actually requires AI.
• Prototyping specifically for learning rather than for production.
• Defining boundaries for AI agents.
• Evaluating AI quality through product-centric metrics.
• Handing off evidence to engineering without pretending a demo is a finished product.

The conceptual workflow for this track follows this sequence: Sense -> Decide -> Learn -> Guardrail -> Specify -> Evaluate -> Build -> Red-team -> Handoff