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tonone
tonone contiene 558 skills recopiladas de tonone-ai, con cobertura ocupacional por repositorio y páginas de detalle dentro del sitio.
Skills en este repositorio
Plan and scope a project — discovery, challenge assumptions, present S/M/L options with token and cost estimates. Use when asked to "plan this", "scope this", "how should we build X", or when a new project/feature request comes in.
Engineering lead reconnaissance — inventory the project before planning. Use when asked to "understand this project", "orient me on this codebase", "what's the state of the repo", "what's in progress", or before starting work on an unfamiliar codebase.
Cross-cutting review of recent work — catches gaps between specialists. Use when asked to "review what we built", "check the work", "pre-launch review", or after completing a significant chunk of work.
CTO-level project status from git and codebase state. Use when asked "where are we", "project status", "what's done", or at the start of a work session.
System takeover — take ownership of an existing codebase or inherited system. Use when "we acquired this", "previous team left", "take over this system", "inherited this codebase".
Write an Architecture Decision Record — document what was decided, why, what alternatives were considered, and what trade-offs were accepted. Use when asked to "write an ADR", "document this decision", or "why did we choose X".
Maintain per-repo and cross-repo changelogs — append structured entries after agent work. Use when asked to "log this change", "update changelog", "what changed", "change history".
Map the system architecture — read the codebase, identify services and connections, output a C4-level architecture map as Mermaid diagrams with component descriptions. Use when asked to "map the architecture", "system diagram", "how does this work", or "architecture overview".
Generate onboarding documentation — what this project does, how to set up locally, where things live, key decisions, how to deploy. Written for day-one engineers who know nothing. Use when asked for "onboarding docs", "new engineer guide", "how to get started", or "developer setup".
Generate a polished HTML presentation page and Obsidian Canvas for big releases — new products, takeovers, major migrations. Non-technical audience. Use when asked to "present this", "release announcement", "show what we built", or "stakeholder update".
Documentation reconnaissance for takeover — find all docs, assess accuracy, freshness, coverage, and discoverability, and identify critical knowledge gaps. Use when asked "what docs exist", "documentation assessment", or "knowledge gaps".
Render agent findings as a styled HTML report in the browser. Use when asked for "full report", "detailed report", "show in browser", or when CLI output exceeds the 40-line budget.
Evaluate model performance — check for accuracy drops, data drift, and error patterns. Use when asked about "model accuracy dropped", "evaluate the model", "check for drift", or "model performance".
Design and implement an AI feature integration — model selection, architecture pattern, system prompt, data flow, error handling, cost estimate. Use when asked to "add AI to this", "LLM integration", "add Claude/GPT", or "AI-powered feature".
Build an ML pipeline — from data to trained model to serving endpoint. Use when asked to "build ML model", "train a model", "prediction pipeline", "classification", or "regression".
Build a production-ready prompt package — system prompt, few-shot examples, output format, edge case handling, eval criteria. Use when asked to "prompt engineering", "build a prompt", "write a system prompt", or "improve this prompt".
ML reconnaissance — inventory all models, pipelines, data sources, and monitoring. Use when asked "what ML do we have", "model inventory", or "ML assessment".
Competitive analysis ending in a clear positioning call — where to play, how to win. Use when asked to "analyze competitors", "competitive landscape", "how do we compare to X", "competitive positioning", "where should we play", "find our white space", or "who else does this".
Strategic narrative — write a standalone strategy memo that frames product direction, bets, and rationale for a planning horizon. Use when asked to "write a strategy doc", "product vision", "strategic narrative", "company strategy memo", "planning memo", or "explain our product direction".
OKR design — create objectives and key results with a North Star metric, input metrics tree, and cadence. Use when asked to "set OKRs", "define our objectives", "what should we measure this quarter", "design our OKR framework", "build a metrics tree", or "what's our North Star".
Strategic context reconnaissance — read existing roadmaps, OKRs, competitive docs, and briefs to establish context before planning. Use when asked to "understand our strategy", "what's the current roadmap", "what OKRs do we have", "strategic context", or before starting any prioritization or roadmap work.
Build a product roadmap with sequenced bets and explicit tradeoffs. Use when asked to "build a roadmap", "prioritize the backlog strategically", "what do we build next quarter", "sequence our bets", "what should we focus on", or "product strategy for the next N months".
Use when asked to design a user flow, map how a user moves through a feature, create a wireframe or flow diagram, or document interaction design for a product brief. Examples: "design the flow for X", "map out the user journey", "create a wireframe for this feature", "how should the UX work for this".
Information architecture — design navigation structure, content hierarchy, sitemap, and taxonomy for a product or feature set. Use when asked to "organize the navigation", "information architecture", "how should content be structured", "sitemap", "nav redesign", "where should X live", or "content hierarchy".
Use when asked to structure a landing page, design page layout for conversion, or plan landing page information architecture. Examples: "landing page structure for SaaS", "conversion-optimized layout"
Use when asked about UX patterns, interaction best practices, form design, navigation patterns, or loading states. Examples: "best practice for form validation", "navigation pattern for dashboard", "loading state UX"
UI and UX reconnaissance — scan existing frontend routes, components, navigation, and flows to understand the current UX state before designing. Use when asked to "understand the current UI", "what UX patterns exist", "map the navigation", "what screens exist", or before starting any flow or wireframe work.
Usability review — evaluate an existing flow or UI against usability heuristics, flag friction points, and recommend fixes. Use when asked to "review the UX", "usability audit", "what's wrong with this flow", "UX feedback", "critique this design", or "why are users dropping off here".
Wireframe a screen — text/ASCII by default, or hand-drawn HTML when the user says "sketch", "hand-drawn", "lo-fi HTML", "whiteboard", "graph paper", or "visual wireframe". Text mode produces a buildable ASCII spec Form and Prism can act on. HTML mode produces a single self-contained file with graph-paper background, marker headlines, sticky-note annotations, and hatched chart placeholders — looks like a designer's whiteboard, commits to nothing.
Feedback synthesis — cluster support tickets, NPS verbatims, app store reviews, and churn surveys by theme, separate signal from noise, and produce an actionable insight report. Use when asked to "synthesize this feedback", "analyze support tickets", "what are users complaining about", "NPS analysis", "churn feedback synthesis", or "what's the feedback telling us".
Run a user interview — produce an interview guide and synthesize the output into an actionable insight report. Use when asked to "run a user interview", "synthesize these interview notes", "what do users actually want", "build a persona from this feedback", "find the JTBD in these transcripts", or "analyze this interview data".
Jobs-to-Be-Done analysis — given a product, user descriptions, transcripts, or tickets, produce a JTBD job map with switching forces analysis and opportunity ranking. Use when asked to "find the JTBD", "what jobs are users hiring us for", "job mapping", "what are users really trying to do", "JTBD framework", or "why are users switching".
User research reconnaissance — survey existing personas, research docs, interview notes, and feedback artifacts to establish what is already known about users. Use when asked to "what research exists", "review existing personas", "what do we know about our users", or before starting new research or synthesis work.
User segmentation and persona creation from mixed data sources — analytics, CRM, support tickets, reviews, or any combination. Use when asked to "build personas", "who are our users", "segment our users", "create user profiles", "define user archetypes", or "who is the target user".
Data quality and pipeline health check — freshness, schema drift, null rates, orphaned records, pipeline status. Use when asked about "data quality check", "pipeline health", "is our data fresh", or "schema drift".
Build zero-downtime database migrations — forward SQL, rollback SQL, deployment sequence. Use when asked to "write migration", "schema change", "add column", "rename table", "drop column", or "migrate safely".
Build a data pipeline — ETL/ELT with extraction, transformation, loading, error handling, and scheduling. Use when asked to "build ETL", "data pipeline", "move data from X to Y", or "sync data".
Optimize slow database queries — analyze execution plans, add indexes, rewrite queries. Use when asked about "slow query", "optimize SQL", "query performance", or "explain this query".
Database reconnaissance — full inventory of schema, migrations, data volume, backups, connection pooling, and query patterns. Use when asked to "assess this database", "understand the schema", or "database health check".
Design and build database schema — tables, columns, types, indexes, constraints, relationships. Given a domain description, output the schema and write the files. Use when asked to "design schema", "database design", "create tables", or "data model".