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Coordinate a research project from a broad topic through literature review, idea selection, experiments, and iterative review. Produce a research summary for writing, with optional paper drafting and PDF compilation, while recording stage progress for later resumption.

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• Taking a broad research topic through experiments and review
• Coordinating experiment implementation and result collection
• Preparing an evidence-based handoff for paper writing

Turn a vague research approach into a concrete method proposal with focused contributions and minimal validation experiments. Ground the plan in relevant papers, then refine it through GPT-6-Astra reviews while preserving the original problem and resource constraints.

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• Turn a rough research idea into an implementable method
• Simplify a proposal with too many components
• Clarify novelty against related research

Create academic architecture diagrams and method illustrations with Gemini image generation. The workflow refines layout and visual style, then uses Claude to inspect arrows, labels, and readability and guide further revisions.

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• Illustrating a model architecture for a paper
• Turning a method description into a workflow diagram
• Reviewing diagram arrows and labels

Explore hardware and electronic design configurations by repeatedly running programs, measuring results, and adjusting parameters. Track constraints and every trial, then report the best configuration found within the time and iteration limits.

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• Tuning cache sizes and processor configuration
• Reducing circuit area while meeting timing constraints
• Comparing compiler flags for runtime or code size

Improve a compiled paper through two rounds of external model review, source edits, and PDF rebuilding. Check claims against evidence, resolve inconsistencies, and refine figures and layout, with optional checkpoints and restrictions on which edits are allowed.

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• Revising a generated paper before submission
• Correcting mismatches between claims and evidence
• Improving notation, figures, tables, and layout

Guides iterative improvement of AI agent prompts, skills, and memory using A-Evolve. It explains how to evaluate agents against benchmark tasks, apply changes, validate results, and track or roll back revisions with Git.

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• Improve an existing agent against benchmark tasks
• Build evaluations for domain-specific tasks
• Refine skills and memory from failure feedback

Build a website one page at a time with Stitch. Each round reads a task file, generates and integrates a page, updates the site plan, and leaves instructions for the next round.

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• Build a site with several pages in repeated rounds
• Keep new pages aligned with a shared design guide
• Add pages following a site roadmap

Check generated PDFs against a page limit or target count, then adjust layout and regenerate as needed. Provides a repeatable workflow for tuning margins, images, tables, and text while respecting readability limits.

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• Keep a report within a page limit
• Fit a map PDF onto one page
• Correct overflow caused by images or tables

Inspect unfamiliar Excel workbooks before building extraction scripts. Map sheets, headers, columns, and row patterns, then use those findings to distinguish actual records from summaries and blank rows when extracting data.

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• Inspecting Excel files received from external sources
• Extracting records from sheets with merged cells
• Investigating missing or unexpected extraction results

Runs repeated reviews and fixes on a Claude Code skill until no critical or major findings remain. Tracks findings across rounds, checks change boundaries, and stops for a design decision when fixes stop making progress.

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• Refining a skill until critical and major findings are resolved
• Improving skill metadata, trigger descriptions, and references
• Tracking recurring findings across review rounds

Co-write proposals, technical specifications, and decision documents through context gathering, section-by-section drafting, and revision. A fresh AI reader then tests the document to reveal unclear explanations, missing context, and contradictions before it is shared.

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• Drafting a proposal through discussion
• Organizing the structure of a technical specification
• Writing a document that explains a decision

Review a branch's commits, combine adjacent changes that belong together, and improve commit messages. A rebuilt history is prepared separately and replaces the original branch only after the user reviews and confirms the proposed changes.

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• Combining unpushed commits on the current branch
• Cleaning up a named branch without checking it out
• Improving unclear commit messages

Structure delegated agent tasks with clear goals, success criteria, and a three-attempt limit. Provides handoff templates and coordinator checks, plus rules for escalating unresolved work and turning research findings into concrete follow-up actions.

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• Preparing clear task briefs for sub-agents
• Checking delegated work against acceptance criteria
• Retrying incomplete tasks with specific corrections

Co-write proposals, technical specifications, and decision documents through context gathering, section-by-section drafting, and revision. A fresh AI reader then tests the document to reveal unclear explanations, missing context, and contradictions before it is shared.

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• Drafting a proposal through discussion
• Organizing the structure of a technical specification
• Writing a document that explains a decision

Design studies that combine quantitative data, such as surveys, with qualitative evidence, such as interviews. It recommends a suitable design and outlines study phases, participant selection, timing, and ways to combine findings into an integrated interpretation.

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• Plan follow-up interviews to explain survey results
• Develop survey measures from interview findings
• Compare quantitative and qualitative findings

Build and test scoring criteria for selecting relevant research papers. Refine the rules against your judgments, screen large sets of abstracts, and reassess saved papers when criteria change, with records of scores and revisions.

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• Define relevance criteria before a large literature search
• Investigate papers incorrectly included or excluded
• Reassess saved abstracts after changing screening criteria

Turn a detailed outline into a philosophy or interdisciplinary manuscript. Draft chapters with repeated quality reviews, check terminology and arguments across sections, and prepare the manuscript, evaluation reports, abstract, and metadata for submission.

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• Draft a full paper from a detailed outline
• Review argument and citation quality chapter by chapter
• Check terminology and argument flow across chapters

Create publication-quality scientific diagrams using Nano Banana 2 AI with smart iterative refinement. Uses Gemini 3.1 Pro Preview for quality review. Only regenerates if quality is below threshold for your document type. Specialized in neural network architectures, system diagrams, flowcharts, biological pathways, and complex scientific visualizations.

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Iterative diagnose-and-fix workflow that repeatedly uses the diagnose skill to find a proven problem, plan the smallest credible improvement, implement it, re-diagnose, and continue until no useful fix remains or user intervention is required. Requires the diagnose skill; selected installs must also install diagnose. Use when asked to keep debugging, fix and verify, iterate until satisfied, improve after diagnosis, or run a diagnosis/fix/verification loop.

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Maintain and patch existing Lark/Feishu documents while preserving comments, highlights, citations, and newer remote edits. Use for iterative document updates, local-mirror sync, or durable project ownership; LoopX integration is optional.

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Optimize code performance through iterative improvements (max 2 rounds). Benchmark execution time and memory usage, compare against baseline implementations, and generate detailed optimization reports. Supports C++, Python, Java, Rust, and other languages.

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工作流组合：当一个任务明显需要多件思想武器接力时，提供四种标准组合模式（新项目启动、复杂问题攻坚、方案迭代优化、阶段复盘），定义调用顺序、每步交接物和终止条件。触发信号包括从零启动、疑难攻坚、迭代优化、阶段复盘；单一 skill 就够用时不触发。 English: Workflow patterns. When a task clearly needs several skills in sequence, pick one of four standard patterns (project kickoff, hard-problem assault, iterative improvement, stage retrospective) that fix the order, the handoff artifact between steps, and the stop condition. Skip when a single skill suffices.

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Self-improving browser automation via the auto-research loop. Iteratively runs a browsing task, reads the trace, and improves the navigation skill (strategy.md) until it reliably passes. Supports parallel runs across multiple tasks using sub-agents. Use when you want to build or improve browser automation skills for specific website tasks.

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Create publication-quality scientific diagrams using Nano Banana Pro AI with smart iterative refinement. Uses Gemini 3 Pro for quality review. Only regenerates if quality is below threshold for your document type. Specialized in neural network architectures, system diagrams, flowcharts, biological pathways, and complex scientific visualizations.

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