Claude Skills by tonone-ai

Design pricing strategy and packaging — tiers, value metrics, enterprise pricing, freemium design, and pricing page copy. Use when asked to "design our pricing", "should we change our price", "how do we package the product", or "what should we charge enterprise".

B2B proposal generator — takes deal context (ICP, pain, pricing tier, timeline) and produces a complete proposal document with executive summary, problem statement, solution, pricing table, implementation timeline, ROI case, and next steps. Use when asked to "write a proposal", "draft our deck for this deal", "build a proposal for this customer", or "generate a proposal".

MEDDPICC-based deal qualification worksheet — guide Deal through structured qualification of any opportunity and produce a filled card + recommended next action. Use when asked to "qualify this deal", "run MEDDPICC on this opportunity", "should we pursue this", or "is this deal real".

Revenue reconnaissance — audit current sales pipeline, deal patterns, ICP definition, and revenue motion to understand what's working and where the constraint is. Use when asked to "audit our sales", "where is revenue stuck", "what's our pipeline state", "before designing a playbook".

Plan and execute canary releases for model updates — traffic splitting, rollback triggers, success metrics.

Audit current model deployment topology — serving config, latency profile, version inventory.

Design and configure model serving infrastructure — endpoint scaling, batching, GPU allocation.

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"

Hi-fi interactive HTML prototype — single-file, double-click-to-open, Playwright-verified. Use when asked to "make it clickable", "build a prototype", "hi-fi mockup", "interactive demo", "iOS prototype", "app mockup", "ui demo", or "prototype this". Goes beyond wireframes into visually finished, state-driven HTML with device frames and real images. Not production code — a design artifact for testing flows and pitching ideas.

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.

Design drift alerts and escalation — thresholds, runbooks, and retrain triggers.

Design a drift monitoring system for a production ML model.

Audit existing ML monitoring — find gaps in drift coverage and missing alerts.

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".

Design a CDN configuration — caching rules, TTLs, and origin shield setup.

Audit existing CDN and edge configuration — find cache misses, missing headers, and performance gaps.

Design an edge routing and geo-distribution strategy — latency routing, failover, and edge logic.

Design embedding pipelines — model selection, batching, normalization, index refresh strategy.

Audit embedding infrastructure — model drift, index freshness, query latency, coverage gaps.

Optimize similarity search — ANN index tuning, hybrid search, reranking, query expansion.

Analyze A/B test results — statistical significance, practical significance, and segmentation.

Design an A/B test — power analysis, randomization, and success metrics.

Audit existing experimentation infrastructure and past experiments for methodology issues.

Design eval harnesses — task schemas, metrics, dataset versioning, eval-as-code patterns.

Build automated regression suites — golden sets, threshold alerting, CI integration for model changes.

Design and implement a feature engineering pipeline for a ML problem.

Audit feature engineering code for leakage, quality issues, and pipeline correctness.

Design or audit a feature store — serving, freshness, and sharing across models.

Audit cloud spend — identify waste, rightsizing opportunities, and reservation gaps.

Survey existing cloud cost controls — tagging coverage, alerting, and FinOps maturity.

Design a reservation and savings plan strategy — commitment level, term, and coverage targets.

Audit existing model training code — find reproducibility issues, data leakage, and missing best practices.

Design a model training pipeline — algorithm selection, cross-validation, and serialization.

Design a hyperparameter tuning strategy for a model — search space, method, and budget.

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".

Design compensation framework - salary bands, equity philosophy, offer templates, and total comp benchmarking. Use when asked to "design our comp bands", "how much equity should we give", "is our comp competitive", or "write an offer template".