개발 스킬

Update an installed Next Move Theory setup to the latest published canon + skills by re-running the official one-command installer straight from the public GitHub repo (zamesin/Next-Move-Theory-Canon-and-Skills, branch main). It refreshes the canon, the nmt-* skills (both Codex and Claude), the marked rules block in AGENTS.md / CLAUDE.md, and the README in place. Idempotent and safe: it never touches your own files and never deletes unrelated skills. Use when the user says "update NMT", "update the skills", "get the latest canon", runs $nmt-update, or when another skill reports that a newer version is available. Defaults to English.

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Update an installed Next Move Theory setup to the latest published canon + skills by re-running the official one-command installer straight from the public GitHub repo (zamesin/Next-Move-Theory-Canon-and-Skills, branch main). It refreshes the canon, the nmt-* skills (both Claude and Codex), the marked rules block in CLAUDE.md / AGENTS.md, and the README — all in place. Idempotent and safe: it never touches your own files and never deletes unrelated skills. Use when the user says "update NMT", "update the skills", "get the latest canon", runs /nmt-update, or when another skill reports that a newer version is available. Defaults to English.

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Turn a chosen segment + Core Jobs into a build-ready PRD (full functionality + edge cases) using Ivan Zamesin's AJTBD / Next Move Theory methodology. Consumes upstream work — segments from $nmt-market-research, value from $nmt-craft-value- proposition — and never re-derives them; with no research it routes you upstream first, or takes a manually described segment+value for a fast run. First runs a "challenge the build" gate that looks for a more effective way to hit the same goal. Output — one PRD mapping Core Job to Big Job to value mechanic to success criteria to Aha Moment on the Critical Chain of Jobs, plus edge cases. Use when the user says "write the PRD / product requirements" or wants to turn a segment+value or feature idea into a build spec. Two modes — Quick (default) and Deep. Defaults to English.

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Extract the AJTBD structure from customer-interview files you already have — segments by Core Jobs, personas, the Consideration Set, existing Solutions and Problems, and value hypotheses — using Ivan Zamesin's Next Move Theory / Advanced Jobs To Be Done methodology. Input — one or many files (transcripts, notes, sales or support calls, survey open-ends), AJTBD or not. It reads each interview in its own context so it never overflows, scores each extraction's confidence, clusters into segments by similar Core Jobs, and writes one report — data-quality summary, segments with personas, structured Solutions and Problems, a Consideration Set, value hypotheses, and what to interview next. Use for "analyze my interviews", "extract jobs from these transcripts", "find the segments in these calls". Defaults to English.

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Talk to a senior product advisor who thinks in Ivan Zamesin's Next Move Theory / Advanced Jobs To Be Done methodology (distinct from generic Christensen JTBD). A multi-turn conversational skill — ask any product, strategy, segmentation, value, pricing, growth, retention, positioning, B2B, or research question and get an answer grounded in the canon, not LLM training. It explains concepts, diagnoses real situations, pressure-tests hypotheses like a skeptical senior PM, and routes heavyweight artifact requests to the right producer skill. Use whenever the user wants advice, a second opinion, a methodology explanation, a diagnosis of "what should I do about X", or to think through a product decision — especially on $nmt-chat. Defaults to English.

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Generate the strongest possible Value Proposition for a chosen segment using Ivan Zamesin's AJTBD / Next Move Theory methodology (distinct from generic Christensen JTBD). Input — a $nmt-market-research result OR a manual segment+Jobs description. It extracts the segment's dominant success criteria, builds the Job Graph + Critical Chain of Jobs, generates value hypotheses via the value-creation mechanics catalog, filters on feasibility, cost, unit economics, and competitiveness, ranks by RICE, and surfaces a primary + supplementary value proposition with top-3 RAT cards and a PRD-ready spec for $nmt-product-requirements. Use when the user wants a value proposition, differentiation, or asks "how do we win this segment". Two modes — Quick (default) and Deep. Defaults to English.

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Write the go-to-market communication for a chosen segment using Ivan Zamesin's AJTBD / Next Move Theory methodology. Input — a $nmt-craft-value-proposition result (best), a $nmt-product-requirements PRD, a $nmt-market-research result, or a manual segment+Jobs description. Output — ready-to-publish landing-page copy, ad/creative copy built on the seven Job-language formulas, and a GTM/growth plan (channel hypotheses, lead magnets, viral loops, cross- sell/upsell/retention). Everything speaks through the Big Job, in concrete success criteria not adjectives, with features as proof. Use when the user wants landing copy, ad copy, creatives, channel hypotheses, or a launch plan — "write the landing / the copy / the go-to-market". Two modes — Quick (default) and Deep. Defaults to English.

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Diagnose a live product against Ivan Zamesin's Next Move Theory / Advanced Jobs To Be Done methodology (distinct from generic Christensen JTBD) and route to the next move. A conversational, chat-first skill: it first offers to read the product context already in your folder (README, surveys, reviews — with your permission), then asks up to ~15 adaptive questions covering only the gaps. It challenges the goal you walked in with, traces weak metrics upstream through the chain to profit, surfaces risks, growth points, and risky assumptions in current initiatives, then recommends which issue to tackle first and which skill executes it. Use when the user says "diagnose my product", "what should I do next", "a metric dropped", "where are my risks / growth points", "where is this breaking", or is unsure what to work on. Writes nothing unless asked; recommends the next skill but the user launches it. Plain language; defaults to English.

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Review tweet drafts in Claude Code against 8 voice rules. Scores 1-10, breaks down every rule, and rewrites anything that scores below 7.

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Generate a clean morning brief in Claude Code — pulls today's priorities, unposted content, and weather from your vault.

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Interact with Google Docs - create documents, search by title, read content, and edit text. Use when user asks to: create a Google Doc, find a document, read doc content, add text to a doc, or replace text in a document. Lightweight alternative to full Google Workspace MCP server with standalone OAuth authentication.

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Generate descriptive commit messages by analyzing git diffs. Use when the user asks for help writing commit messages or reviewing staged changes.

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Model Context Protocol (MCP) integration specialist. Use when creating MCP server configurations, implementing MCP integrations, or optimizing MCP performance. Specializes in MCP server architecture and integration patterns.

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Python scripting with uv and PEP 723 inline dependencies. Use when creating standalone Python scripts with automatic dependency management.

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Comprehensive debugging specialist for errors, test failures, log analysis, and system problems. Use when encountering issues, analyzing error logs, investigating system anomalies, debugging production issues, analyzing stack traces, or identifying root causes. Combines general debugging workflows with error pattern detection and log analysis.

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Enterprise-level Go architecture patterns including clean architecture, hexagonal architecture, DDD, and production-ready application structure.

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SQL query optimization and database performance specialist. Use when optimizing slow queries, fixing N+1 problems, designing indexes, implementing caching, or improving database performance. Works with PostgreSQL, MySQL, and other databases.

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Detects and safely removes unused code (imports, functions, classes) across multiple languages. Use after refactoring, when removing features, or before production deployment. Includes safety checks and validation.

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Expert code review specialist for quality, security, and maintainability. Use when reviewing code changes, ensuring high development standards, or conducting security audits. Provides actionable feedback organized by priority.

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Project-wide coding standards and conventions specialist. Use PROACTIVELY when writing code, making architectural decisions, or establishing project conventions. Covers coding style, commenting, error handling, validation, tech stack consistency, and project conventions across all languages and frameworks.

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Automatically find relevant context from knowledge graph and code relationships while coding. Detects when context would be helpful (new files, unfamiliar code, architectural decisions) and surfaces related entities, prior decisions, and code dependencies.

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Remove AI-generated code slop from branches. Use after AI-assisted coding sessions to clean up defensive bloat, unnecessary comments, type casts, and style inconsistencies. Focuses on identifying and removing AI artifacts that degrade code quality.

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Go performance optimization techniques including profiling with pprof, memory optimization, concurrency patterns, and escape analysis.

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Next.js architecture specialist. Use when designing Next.js applications, migrating to App Router, implementing Server Components, or optimizing Next.js performance. Covers App Router, Server Components, and best practices.

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