Results for “recommendations”

Comprehensive guide for discovering, understanding, and installing Claude Code skills from skills.sh marketplace. Use this skill when users want to (1) browse or search skills.sh for recommendations, (2) get skill recommendations by role (developer, marketer, designer, product manager), (3) understand how a specific installed skill works by reading and explaining its SKILL.md, (4) learn the anatomy and structure of skills, or (5) find and install skills that match their specific workflow needs. This is NOT for creating new skills (use skill-creator instead).

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Generates sustainability-focused guidance for Google Cloud workloads based on the design principles and recommendations in the Google Cloud Well-Architected Framework (WAF). Use this skill to evaluate a workload, identify environmental impact requirements, and provide actionable recommendations to build, deploy, and manage the workload sustainably in Google Cloud.

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Generates security-focused guidance for Google Cloud workloads based on the design principles and recommendations in the Google Cloud Well-Architected Framework (WAF). Use this skill to evaluate a workload, identify security requirements, and provide actionable recommendations for IAM, network security, data protection, and operational security.

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Generates operations-focused guidance for Google Cloud workloads based on the design principles and recommendations in the Operational Excellence pillar of the Google Cloud Well-Architected Framework (WAF). Use this skill to evaluate a workload, identify operational requirements, and provide actionable recommendations for deployment, monitoring, and incident management.

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Generates reliability-focused guidance for Google Cloud workloads based on the design principles and recommendations in the Google Cloud Well-Architected Framework. Use this skill to evaluate a workload, identify reliability requirements, and provide actionable recommendations for build, deploy, and manage the workload reliably in Google Cloud.

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Generates performance-focused guidance for Google Cloud workloads based on the design principles and recommendations in the Performance Optimization pillar of the Google Cloud Well-Architected Framework (WAF). Use this skill to evaluate a workload, identify performance requirements, and provide actionable recommendations for resource allocation, modular design, and elasticity.

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Use for deep Vue 3 best-practices review, recommendations, and the full ordered authoring workflow — built-in components (Teleport, Suspense, KeepAlive, Transition, TransitionGroup), animation techniques, slots, fallthrough attrs, custom directives, async components, render functions, plugins, and the post-functionality performance pass. Complements mk:vue (the everyday Composition API quick-reference). Invoke for "review my Vue", "Vue best practices", "recommend improvements", or non-trivial feature work needing the ordered workflow.

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This skill should be used when analyzing bug ticket data to identify quality trends, assess software quality status, and provide improvement recommendations. Use when a user provides bug lists (CSV, Excel, JSON, or Markdown format) and needs comprehensive quality analysis from a QA manager perspective. Generates statistical analysis, identifies quality hotspots, provides actionable recommendations, and produces professional Markdown reports suitable for project managers and executive leadership. Ideal for IT system development, migration, and implementation projects.

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Review Claude skills and commands for usefulness, overlapping content, and outdated technical references. Choose a scan of changed skills or a full review, then receive reasoned recommendations to keep, improve, update, retire, or merge them.

• Reviewing all installed skills
• Checking only recently changed skills
• Finding overlapping skill content

Research current facts, compare options, or investigate people and companies using public sources and supplied context. This skill selects an appropriate research workflow and separates evidence, inference, and recommendations, including dates where freshness matters.

• Check current facts against existing documents
• Compare options before making a decision
• Research potential contacts and companies

Add machine learning to an existing application through a structured workflow. The skill guides problem definition, data checks, separation from business logic, and training and evaluation of a simple initial model.

• Adding recommendations to an existing application
• Checking whether training data is ready
• Integrating a prediction model with fallback rules

Research markets, competitors, investors, and technologies to support business decisions. Produces sourced findings, market size estimates, and recommendations that distinguish facts from assumptions while including risks, conflicting evidence, and limits in the available data.

• Estimating market size before entering a market
• Comparing competitors and their positioning
• Researching investors before approaching them

Refine interface appearance and interactions by reviewing spacing, typography, rounded corners, shadows, animation, and clickable areas. Get concrete before-and-after recommendations for buttons, cards, forms, and other components, including hover, focus, and loading states.

• Review screens that feel cramped or unfinished
• Refine buttons, cards, and forms
• Improve hover, focus, and loading states

Audit Claude Code agents, skills, rules, and MCP tool configurations to estimate how much space they consume in the model's context. Identifies oversized and overlapping components, then ranks recommendations by potential token savings.

• Investigating why context space fills quickly
• Auditing a setup after adding skills or MCP servers
• Finding oversized files and duplicated instructions

Review X and LinkedIn relationships against current priorities. Receive ranked suggestions for accounts to remove, keep, or add, plus outreach drafts in your own voice for X, LinkedIn, or Apple Mail, ready for review.

• Reviewing X accounts to unfollow
• Rebalancing LinkedIn relationships
• Finding people to follow for current priorities

Test a plan before implementation through structured, challenging questions. Work through decisions in dependency order, receive recommendations with each question, and finish with a clear account of agreed choices, open issues, and scope.

• Clarifying an idea before implementation
• Testing authentication or payment plans
• Examining failure scenarios and rollback options

Build similarity search with Qdrant, a database for numerical representations of content. Store and retrieve vectors, filter results by metadata, connect retrieval to AI answers, and configure memory usage and deployment for larger workloads.

• Retrieving reference documents for AI answers
• Filtering similarity search by category or date
• Building real-time recommendations

Test an idea before committing to a full build through disposable prototypes. The skill turns uncertainties into concrete experiments, compares approaches, checks edge cases, and records evidence, limitations, and recommendations for implementation.

• Testing whether an idea is technically feasible
• Comparing libraries through working prototypes
• Checking risky assumptions before development

Add two or three specific follow-up questions after actionable advice, plans, estimates, or analysis. The questions help users examine facts, reasoning, and missing context before acting, with clear exclusions and a limit of once per conversation.

• Examining assumptions behind cost or timeline estimates
• Checking reasoning behind a recommended plan
• Spotting missing context in proposals or email drafts

Compare a Git diff with its stated purpose to flag potentially unrelated files, added dependencies, API renames, and configuration changes. Receive recommendations to keep, split, or justify changes, with a proposed grouping for follow-up work.

• Check scope before opening a pull request
• Find unexpected changes in a bug fix
• Review whether staged changes are too broad

Review an implementation plan before coding, checking system structure, data flow, diagrams, edge cases, test coverage, and performance. Discuss issues interactively with concrete recommendations to settle technical decisions before implementation begins.

• Reviewing an implementation plan before coding
• Checking system structure and data flow
• Reviewing edge cases and test coverage

Review recent development work to find code worth sharing across existing callers. Receive ranked recommendations backed by verified source locations, estimated line savings, migration steps, and risks, without changing files or running project code.

• Find repeated code in recent changes
• Compare code savings and risks before sharing helpers
• Check whether existing PRs already cover a proposed extraction

Define a new product's visual style through product discovery and research. Get recommendations for fonts, colors, layout, spacing, and motion, preview font and color combinations, and document the shared design rules in DESIGN.md.

• Defining the visual style for a new product
• Documenting shared brand and interface guidelines
• Previewing font and color combinations

Work through complex or costly decisions with a structured process covering context, research, competing perspectives, planning, execution, and critical review. The workflow adapts its depth to the task and produces recommendations with tradeoffs, risks, and success criteria.

• Comparing system architecture options
• Planning changes across multiple systems
• Rechecking assumptions in an ambiguous request