market-sizing
TAM/SAM/SOM calculator with deep market research. Produces comprehensive market-sizing.md with top-down and bottom-up estimates, methodology, data sources, assumptions, sensitivity ranges, growth projections, competitive landscape, and Mermaid visualizations. Use when user needs market size estimates, addressable market analysis, go-to-market sizing, investor-ready market analysis, or business plan market validation.
What this skill does
# Market Sizing Agent Produce rigorous, investor-grade TAM/SAM/SOM analyses by combining top-down macro data with bottom-up unit economics, triangulating the two, and always showing the work, citing sources, flagging assumptions, and providing sensitivity ranges. ## Contents - `references/research-sources.md` — source categories and search queries for every research lane. - `references/methodology.md` — top-down, bottom-up, triangulation, sensitivity, growth, competitive sizing, and pitfalls. - `references/output-template.md` — the full `market-sizing.md` document template, Mermaid charts, and quality checklist. ## Inputs Confirm these four inputs before proceeding. If any is missing or ambiguous, ask first. | Parameter | Description | Example | |---|---|---| | **Industry** | The broad industry or sector | "Enterprise SaaS", "Electric Vehicles" | | **Product/Service** | The specific offering being sized | "AI-powered code review tool" | | **Geography** | Target market geography | "United States", "Global", "DACH region" | | **Target Segment** | The specific customer segment | "Mid-market companies (100-1000 employees)" | ## Workflow 1. Confirm the four inputs with the user; resolve any ambiguity before research. 2. Research first. Gather and cite data across all four lanes (industry data, competitor revenue, growth rates, unit economics). See `references/research-sources.md`. Log every source URL and date as you go. 3. Run the top-down calculation: broadest market figure, then geographic, segment, and product-fit filters, then a realistic SOM capture rate. See `references/methodology.md`. 4. Run the bottom-up calculation: customer count times average revenue per customer, narrowed to reachable and obtainable. See `references/methodology.md`. 5. Triangulate top-down and bottom-up, explain any divergence over 2x, and produce a weighted best estimate. 6. Run sensitivity analysis: conservative, base, and aggressive scenarios plus the top 3-5 swing variables. 7. Project market size forward 5 years and size the competitive landscape (share distribution, top competitors, barriers, positioning). 8. Generate `market-sizing.md` using the structure in `references/output-template.md`. Show all math, cite every figure, and verify against the quality checklist before delivering. 9. Present the result, then offer to adjust assumptions, explore alternative market definitions, or drill deeper. ## Rules - Show all math; never present a number without showing how it was derived. - Cite every data point with a source URL and date; prefer data from the last 12-24 months and flag anything older. - Flag uncertainty explicitly when data is sparse or conflicting. Never fabricate precision. - Triangulate from at least 2-3 independent sources when possible. - Normalize all figures to a single currency and base year. - No emojis anywhere in the output. Avoid the pitfalls listed in `references/methodology.md`.
Related in Ads & Marketing
ads
IncludedMulti-platform paid advertising audit and optimization skill. Analyzes Google, Meta, YouTube, LinkedIn, TikTok, Microsoft, and Apple Ads. 250+ checks with scoring, parallel agents, industry templates, and AI creative generation.
banana
IncludedAI image generation Creative Director powered by Google Gemini Nano Banana models. Use this skill for ANY request involving image creation, editing, visual asset production, or creative direction. Triggers on: generate an image, create a photo, edit this picture, design a logo, make a banner, visual for my anything, and all /banana commands. Handles text-to-image, image editing, multi-turn creative sessions, batch workflows, and brand presets.
rpg-migration-analyzer
IncludedAnalyzes legacy RPG (Report Program Generator) programs from AS/400 and IBM i systems for migration to modern Java applications. Extracts business logic from RPG III/IV/ILE source code, identifies data structures (D-specs), file operations (F-specs), program dependencies (CALLB/CALLP), and converts RPG constructs to Java equivalents. Generates migration reports, complexity estimates, and Java implementation strategies with POJO classes, JPA entities, and service methods. Use when modernizing AS/400 or IBM i legacy systems, analyzing RPG source files (.rpg, .rpgle, .RPGLE), converting RPG to Java, mapping data specifications to Java classes, planning legacy system migration, or when user mentions RPG analysis, Report Program Generator, RPG III/IV/ILE, AS/400 modernization, IBM i migration, packed decimal conversion, or mainframe application rewrite.
brand-library-architect
IncludedBuild a complete brand library for a product — visual asset render pipeline, brand documentation set (BRAND, COPY, MANIFESTO, BIOS, FAQ, GLOSSARY, TONE, PRICING), open-source convention files (README, CONTRIBUTING, SECURITY, CODE_OF_CONDUCT), and a self-contained press kit. This skill should be used when the user asks to "build a brand library / brand kit / press kit / brand assets" for a product, "set up a brand library workflow," "create a positioning manifesto plus visual identity," or any combination of brand documentation + visual asset pipeline. Apply phase-by-phase or run end-to-end. Templates are product-agnostic and use {{TOKEN}} placeholders the skill prompts the user to fill.
writing-tech-post
IncludedAuthors engineering blog posts end-to-end: launch deep-dives, incident postmortems, architecture migrations, performance case studies, tutorials, AI/agent system writeups, security disclosures, and research-to-product translations. Picks the correct archetype, plans the abstraction ladder, enforces an evidence cadence (diagrams, benchmarks, profiles, traces, code, ablations), tunes voice against publisher house styles (Datadog, Vercel, GitHub, AWS, Meta, Cloudflare, Jane Street), and runs a pre-publish gate for narrative momentum and disclosure ethics. Use when drafting a new engineering post, restructuring a draft that feels flat, deciding which evidence form belongs where, validating that depth and product context are balanced, or preparing a postmortem, migration, or performance narrative for external publication. Do not use for API reference documentation, README authoring, marketing copy, release notes, generic SEO content, ghost-written executive thought leadership, or non-engineering long-form essays.
blog-google
IncludedGoogle API integration for blog performance: PageSpeed Insights, CrUX Core Web Vitals with 25-week history, Search Console performance, URL Inspection, Indexing API, GA4 organic traffic, NLP entity analysis for E-E-A-T, YouTube video search for embedding, and Google Ads Keyword Planner. Progressive feature availability based on credential tier (API key, OAuth/service account, GA4, Ads). Shares config with claude-seo at ~/.config/claude-seo/google-api.json. Use when user says "google data", "page speed", "core web vitals", "search console", "indexation", "GA4", "keyword research", "nlp entities", "blog performance", "youtube search", "google api setup".