TAM Analysis Skill

This is an AI-agnostic research workflow for estimating Total Addressable Market with transparent assumptions, multiple sizing methods, confidence ranges, and source-backed calculations.

The skill is portable across AI tools. Use it with ChatGPT, Claude, Gemini, Perplexity, Manus, Codex, Cursor, local models, browser-based research, note-taking systems, spreadsheets, or manual research.

What It Helps With

• Define TAM boundaries precisely enough to be useful
• Estimate market size with top-down, bottom-up, and segment/income-based approaches
• Track assumptions, formulas, units, and confidence ranges
• Translate customer counts into revenue opportunity using price, adoption, and lifetime assumptions
• Produce investor- and strategy-ready market-sizing narratives

Why It Exists

Research templates are useful, but assistants often fill them with plausible-sounding generalities unless they are forced to track evidence, assumptions, gaps, and strategic implications. This skill turns the source template into an operating workflow: gather the right inputs, structure the research, mark uncertainty, and produce an artifact that can guide real decisions.

Repository Contents

.
|-- SKILL.md
|-- README.md
|-- assets/
|   `-- tam-analysis-banner.png
|-- agents/
|   `-- openai.yaml
`-- references/
    `-- source-template.md

• SKILL.md is the installable skill.
• references/source-template.md preserves the original Nessie template that inspired the workflow.
• agents/openai.yaml is optional UI metadata for OpenAI/Codex-style skill surfaces.

Quick Start

Give an assistant the contents of SKILL.md, then ask it to produce or improve the research artifact.

Example:

Use the TAM Analysis skill to turn the notes below into a clear, evidence-backed research artifact. Mark assumptions and gaps instead of inventing facts.

For tools that support skill folders, install or copy this folder into the tool's skills directory and invoke:

Use $tam-analysis to estimate the TAM for this product with clear assumptions and sources.

Recommended Process

1. Clarify the product, audience, market, and decision the research should support.
2. Gather supplied material and current external sources when available.
3. Separate evidence from assumptions.
4. Draft the research artifact using the skill's output sections.
5. Audit the artifact for unsupported claims, vague categories, stale data, and missing next steps.

GitHub Description

AI-agnostic research skill for defensible TAM analysis using top-down, bottom-up, and triangulated market-sizing methods.

Suggested GitHub Topics

ai, ai-agents, research, market-research, tam, market-sizing, total-addressable-market, business-strategy, startup, fundraising, gtm, bottom-up-analysis, top-down-analysis, financial-modeling, prompt-engineering, ai-skills

Source Inspiration

This package was created from the shared Nessie context TAM Template, then rewritten as portable, AI-agnostic agent instructions.

License

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