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Design and build AI agents for business, research, operations, or creative work. Define essential actions and knowledge, start with a simple execution loop, and add progress tracking or separate child agents as needs emerge.
中文简介正在准备中。当前显示英语简介。
Build complex claude.ai artifacts with React, Tailwind CSS, and shadcn/ui. Create interfaces with multiple components, state management for changing data, and routing between views, then package the app into one self-contained HTML file for sharing.
中文简介正在准备中。当前显示英语简介。
Coordinate multiple AI agents for feature development or refactoring across several files. The skill guides team setup, task assignment, status checks, and recording successful approaches for use in later work.
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Organize new features, complex implementations, and architecture changes into the SPARC stages: specification, pseudocode, architecture, refinement, and completion. Define requirements and acceptance criteria, consult existing patterns, and record lessons for future work.
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Choose an agent and model tier using the task description and learned patterns. The skill can explain its recommendation, use compiler-based edits for supported simple changes, and record task outcomes to inform future routing decisions.
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Assess tasks before execution to identify transformations eligible to skip LLM calls. Report the eligible share, recommended models for remaining tasks, and estimated upper costs, then save the routing results for later cost reports.
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Review messages that display counts and check whether each target language gets the correct plural form. Replace simple number-and-text joins or singular/plural branches with Intl.PluralRules or ICU MessageFormat, which select wording according to language-specific rules.
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Retrieve pages blocked by web access filters, read Chinese and social platforms through dedicated tools, and inspect archived copies with their dates. Escalate to browser interaction when simpler extraction methods cannot provide the needed content.
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Explore design ideas with three to five distinct rough options using wireframes, simple screen layouts, and storyboards. Compare structure and flow, then develop selected options while keeping earlier rounds available for reference.
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Plan game development workflows by matching engines, art and audio tools, automated playtests, packaging, publishing, and analytics to available tools and credentials. Compare options by cost, quality requirements, and offline availability.
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Read, analyze, modify, and visualize molecular structures with RDKit in Python. Calculate molecular properties, search for similar structures or specific structural patterns, apply reaction rules, and generate 2D or 3D coordinates with detailed control over processing.
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Process mass spectrometry data using scripts for format conversion, signal cleanup, peak detection, and quantification across samples. Prepare protein and metabolite analyses with identification filtering, candidate annotations, data tables, and plots.
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Look up genes, sequences, protein structures, expression patterns, and disease associations across more than 20 bioinformatics resources using command-line tools or Python. Useful for interactive exploration, with results that can be saved for further analysis.
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Retrieve public evidence and linked publications for a supported genetic variant, or look up gene–disease relationships. Preserve sources, conflicting assertions, and explicit search outcomes so qualified professionals can review the findings.
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Process molecular datasets in Python through a simpler interface to RDKit, a chemistry toolkit. Convert and standardize structures, calculate molecular properties, compare and cluster compounds, generate 3D conformations, and visualize results for drug discovery workflows.
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Rebuild slide images, screenshots, scanned PDFs, or image-only presentations as editable PowerPoint files. Reconstruct text and simple shapes as separate objects, retain complex visuals as image assets where needed, and check rendered slides against their sources.
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Plan a simple daily attendance register covering check-in, check-out, hours, absences, and correction requests. When requested, generate empty templates in CSV, SQL, JSON Schema, or Notion mappings to prepare records for payroll input.
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Plan a former employee register covering previous roles, departure dates, rehire eligibility, and future contact dates. Receive a simple workflow recommendation, with empty CSV templates, SQL table definitions, JSON Schema, or Notion mappings available on request.
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Guide AI coding work toward simple implementations, focused edits, and explicit assumptions. Use it when writing, reviewing, or refactoring code to keep changes tied to the request and define success through tests or other concrete checks.
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Design and refactor Python components with clear responsibilities and simple structure. Assess when to split large classes, combine objects instead of extending them, and extract shared code without introducing unnecessary abstractions.
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Finds a local MCP server, a connector that adds tools to an agent, when existing tools or simple code cannot handle a task. It selects packages requiring no environment variables and starts them after approval.
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Turn company documents, public filings, and other sources into structured Excel workbooks for investment review. Organize financial statements and operating metrics, document sources and adjustments, and check that calculations and statements reconcile.
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Use OpenViking MCP tools to retrieve relevant knowledge before substantial tasks and save lasting preferences, decisions, and lessons during or after work. Import documents as searchable resources so later tasks can draw on previous findings.
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Retrieve past operational experience from OpenViking before or during coding, configuration, deployment, or recovery work. It reads relevant records, checks whether their assumptions match the current environment, and applies suitable procedures and checks.
中文简介正在准备中。当前显示英语简介。