“recommendations”的搜索结果

Read a book, article, transcript, or case study against a specific strategic problem. The skill turns relevant passages into practical actions, countermeasures, and warning signs, with source evidence and recommendations for the short, medium, and long term.

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• Applying lessons from a book to a current business problem
• Learning tactics and countermeasures from historical cases
• Turning an article or transcript into an action plan

Audit instructions and memory files loaded on every agent turn. Identify repeated rules, contradictions, outdated content, and material better moved into skills, then receive evidence-backed recommendations ranked by estimated token savings and change risk.

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• Reduce the size of instructions loaded on every turn
• Find conflicting rules across instruction and memory files
• Identify workflow instructions to move into separate skills

Turn marketing results into a report with key metrics, comparisons over time, wins, and areas to improve. Prioritize recommendations by expected impact and effort, then outline the next period’s actions for teams or leadership.

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• Reviewing results after a marketing campaign
• Preparing weekly or monthly channel reports
• Summarizing marketing performance for leadership

Draft marketing content for blogs, social platforms, newsletters, landing pages, press releases, and case studies. Adapt the format and tone to the audience and brand, with headline or subject options and search visibility recommendations for web content.

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• Draft a blog post with headline options and SEO suggestions
• Adapt a message for a specific social platform
• Write a newsletter with subject line options

Turn interview notes, survey responses, and customer feedback into findings supported by evidence. Group recurring themes, assess frequency and impact, and produce prioritized recommendations to guide product improvements and future research.

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• Finding shared issues across user interviews
• Organizing themes in open-ended survey responses
• Prioritizing improvements from support tickets

Plan user research, prepare interview guides, and organize findings into themes and recommendations. Choose methods suited to the question, such as interviews, surveys, or usability tests that examine how people use a design.

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• Planning research into user needs and motivations
• Preparing an interview guide
• Designing usability tests or surveys

Turn interviews, surveys, usability notes, and customer feedback into shared themes, user groups, and prioritized recommendations. Findings include supporting quotes and participant counts, helping teams connect research evidence to concrete product improvements.

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• Find common issues across user interviews
• Combine survey results and support feedback
• Prioritize product improvements using research evidence

Check the state of an agent’s project memory with a dashboard of line counts, topic files, capacity, outdated file references, and duplicates. Get cleanup recommendations or request a one-line status summary.

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• Checking how full project memory is
• Finding references to deleted files
• Reviewing memory and rule file sizes

Turn an electronics or IoT idea into a working breadboard prototype. Get board and software recommendations, a plan for viewing sensor readings, and time and cost ranges tailored to experience, budget, and location.

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• Choosing a board and development tools for a first electronics project
• Planning phone access to sensor readings and alerts
• Estimating prototype costs and build time

Assess a product or business through SWOT: strengths, weaknesses, opportunities, and threats. Connect internal capabilities with market conditions to develop strategic recommendations, prioritize actions, identify owners, and define measures for tracking progress.

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• Assessing a product's competitive position
• Reviewing strategy as market conditions change
• Prioritizing partnerships and resource allocation

Compare feature ideas by expected impact, required effort, uncertainty, and fit with product goals. Get five ranked recommendations, with reasons for each choice, trade-offs, and explanations of which ideas should receive lower priority.

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• Ranking a backlog of feature ideas
• Choosing the scope of the next development cycle
• Comparing opportunities using customer importance and satisfaction

Review game code for likely performance bottlenecks in processing, memory, rendering, and data loading. Compare available estimates with configured limits and produce ranked optimization recommendations, including expected impact, effort, risks, and areas needing runtime measurement.

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• Finding performance bottleneck candidates in one game system
• Reviewing performance across the whole game
• Comparing available estimates with configured performance limits

Assess Google Cloud workloads for environmental sustainability using the Well-Architected Framework. Get recommendations on lower-carbon regions, efficient computing and storage, AI energy use, and ongoing emissions measurement with Carbon Footprint.

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• Reviewing cloud architecture for environmental impact
• Comparing deployment regions by carbon-free energy use
• Reducing energy waste in AI and computing workloads

Evaluate Google Cloud workloads and develop reliability recommendations covering user experience goals, redundancy, monitoring, and recovery. The skill applies the Google Cloud Well-Architected Framework to help identify gaps and plan improvements suited to business requirements.

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• Reviewing a Google Cloud architecture for reliability gaps
• Setting reliability targets based on user experience
• Planning redundancy and behavior during partial failures

Design a Google Cloud system that combines multiple services, starting with a discussion of business and technical requirements. The skill produces service recommendations, architecture diagrams, deployment guidance, and validation plans, with user approval at each stage.

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• Gather requirements for a new cloud workload
• Compare and select services for a cloud migration
• Create a diagram and explain system data flows

Build search and recommendation features with Pinecone, a managed database for numerical representations of content. Covers data loading, combined meaning and keyword search, filtering by attributes, and separating data by user.

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• Build document retrieval for AI answers
• Combine meaning and keyword search
• Separate search data by user

Assess a brand’s presence on YouTube, Reddit, Wikipedia, LinkedIn, and other sources relevant to AI search. Review mentions, official profiles, and discussion sentiment, then produce a weighted authority score and recommendations for each platform.

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• Reviewing brand mentions across major platforms
• Assessing positive and negative Reddit discussions
• Checking Wikipedia and Wikidata presence

Check whether AI crawlers, the bots that collect web content for AI services, can access a website. Get a crawler access table, an assessment score, and recommendations based on robots.txt, page tags, HTTP headers, and rendering requirements.

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• Checking which AI crawlers can access a website
• Reviewing unintended blocks in robots.txt
• Investigating content that requires JavaScript to display

Turn interviews, surveys, usability notes, and customer feedback into shared themes, user groups, and prioritized recommendations. Findings include supporting quotes and participant counts, helping teams connect research evidence to concrete product improvements.

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• Find common issues across user interviews
• Combine survey results and support feedback
• Prioritize product improvements using research evidence

Plan user research, prepare interview guides, and organize findings into themes and recommendations. Choose methods suited to the question, such as interviews, surveys, or usability tests that examine how people use a design.

中文简介正在准备中。当前显示英语简介。

• Planning research into user needs and motivations
• Preparing an interview guide
• Designing usability tests or surveys

Review TikTok Ads measurement, mobile video creative, audiences, commerce campaigns, bidding, and budgets. Receive prioritized recommendations with supporting evidence, missing information, and uncertainty clearly identified, while keeping the review read-only.

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• Checking TikTok Pixel and conversion measurement
• Reviewing mobile video creative and audiences
• Auditing Smart+ and TikTok Shop Ads

Turn data findings into reports and presentations that explain why the numbers matter. The skill combines context, problems, recommendations, and visual guidance to help executives and nontechnical audiences understand evidence and decide on next steps.

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• Explaining analysis results to executives
• Structuring quarterly business reviews
• Building investor presentation narratives

Submit shopping questions to Amazon's Alexa/Rufus assistant and collect answers as JSON, a structured data format. Use product search results as context for category research, or run a series of general shopping questions.

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• Collecting product recommendations for a specific category
• Gathering answers to a batch of shopping questions
• Researching deals and shopping trends

Inspect scientific data files to understand their format, structure, and quality. Covering over 200 formats, this skill produces Markdown reports with statistical summaries, potential issues, and recommendations for preprocessing, visualization, and further analysis.

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• Inspecting an unfamiliar scientific data file
• Checking missing values and duplicates in experimental tables
• Reviewing sequence lengths and quality scores in FASTQ files