“ai-assisted”的搜索结果

为AI修改的代码补充回归测试，自动检查API必需字段和处理分支，并建立先运行测试与构建、再进行AI审查的流程，检测已修复问题是否再次出现。

• 修复缺陷后补充回归测试
• 检查API响应中的必需字段
• 核对测试与生产环境的响应

Inspect a project's code, history, tests, and documentation, then ask three focused questions to recommend an AI-assisted development approach. Receive one combination of methods, reasons for the choice, and practical first steps tailored to the project.

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• Choosing an AI-assisted workflow for a new project
• Reviewing development methods for an existing service
• Aligning specifications and tests across services

Refine AI-assisted academic drafts into natural scholarly prose while preserving citations, statistics, and methodological details. Choose how extensively to revise and which sections to edit, then review a report comparing the original and revised text.

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• Polishing an AI-assisted academic draft
• Making minimal edits before journal submission
• Revising only the abstract and discussion

Evaluate performance fairly when output is AI-assisted — what still measures the human, what now measures the tooling, and how to run the review conversation. Use when reviewing someone whose work is heavily AI-assisted, when output volume stopped meaning anything, when calibrating a team with uneven AI adoption, or when writing review criteria for the AI era. Produces review guidance: a what-measures-whom analysis, rewritten criteria, calibration rules for mixed-adoption teams, and conversation scripts. For the general review document use performance-review; for redesigning the role itself use role-redesign-for-ai.

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Open the hosted context-mode Insight dashboard in your default browser to access analytics for AI-assisted engineering teams, including productive rates per engineer, retry waste, blockers, and views tailored to different roles.

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• Opening the team's development analytics dashboard
• Reviewing productive rates and retry waste per engineer
• Checking blockers and views tailored to team roles

Set up and use CircleCI Chunk for AI-assisted build and delivery workflows. Chooses web or command-line steps for configuration, failed-build troubleshooting, environment setup, and task execution, then reports results and unmet prerequisites.

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• Set up Chunk and a model provider
• Investigate and fix failed builds
• Configure project environments

Turn AI-assisted coding work into optional, short learning exercises. Predict behavior, compare your approach with the implementation, or explain code in your own words, with feedback that helps clarify how the code works and why design choices were made.

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• Understanding a newly created module
• Reviewing the reasoning behind a design decision
• Checking understanding after a database schema change

Plan AI-assisted ad creative production, testing, budget allocation, and measurement across advertising platforms. It provides workflows for comparing messages, adapting assets to each channel, and refreshing ads when repeated exposure starts to reduce performance.

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• Planning AI-assisted ad image and video production
• Testing opening hooks, narratives, and calls to action
• Refreshing ads as repeated exposure reduces performance

Examines project code, development history, tests, and documentation, then asks three focused questions to recommend a combination of AI-assisted development methods, with practical starting steps tailored to the project.

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• Choosing development methods for a solo prototype
• Reviewing workflows for an existing SaaS product
• Selecting evaluation methods for an AI product

Improve the clarity and voice of AI-assisted academic writing (papers, theses, rebuttals) and funding proposals (NSF Project Summary/Description, NIH Specific Aims): preserve scholarly conventions, match claims to evidence (and, for proposals, claims to feasibility), and match the author's own voice. It never changes a number, result, or citation, and it is not for evading AI-use disclosure. Use when editing AI-assisted academic prose or grant proposals.

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Design an AI-assisted workflow for a recurring task — which steps to hand to AI, which to keep human, and how they connect — so you get leverage without losing quality or control. Use when asked how do I use AI for [process], automate this with AI, design an AI workflow, or where does AI fit in my process. Produces a map of the task's steps split into AI-does / human-does / human-checks, the right tool/prompt for each AI step, the hand-offs and review points, the failure modes to guard against, and a start-small rollout — turning a manual process into a reliable AI-assisted one that keeps you in control.

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Research and prepare an outside contribution to an open-source repo, then stop at a queue item for a human to approve: policy check, intake, duplicate check, reproduction, patch, the repo's own checks, an independent critic rerun, and a disclosed, hashed draft of the exact text to post. Use this skill whenever the user wants to contribute to someone else's repo, fix an upstream bug, pick up a good-first-issue, draft an AI-assisted pull request for an outside project, follow up on their own outside PR, or run a gated contribution pipeline. Triggers on open source contribution, contribute to this repo, upstream fix, outside PR, external PR, good first issue, fix this issue in their repo, contribution research, AI-assisted PR, disclose AI in PR, reply to review on my PR. Also triggers when the user names an issue in a repo they do not maintain and asks for a fix, even if they do not say contribute.

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How humans and AI compose in content workflows. Where AI legitimately participates, where humans must own, hybrid workflow patterns, voice ownership preservation, the AI slop problem, disclosure and transparency, team calibration, and the ethics of intellectually honest AI-assisted content production. Triggers on AI content workflow, AI-assisted writing, hybrid content production, AI in editorial, AI slop, AI disclosure, AI usage policy, AI content ethics, voice preservation with AI, team AI calibration. Also triggers when content feels generic despite quality tools, when team AI usage has drifted into inconsistency, or when a regulated or trust-sensitive context requires explicit AI policy.

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Systematic strategies for searching scientific literature across PubMed, arXiv, Google Scholar, and AI-assisted tools. Covers PICO framework for clinical questions, three-tiered search (database-specific, AI-assisted, content extraction), PubMed field tags and MeSH, boolean query construction, and full-text extraction. Use when planning a literature search or choosing a search tier.

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从已有视频和屏幕录制中选择精彩片段，完成剪切、结构整理、字幕与音频添加，涵盖长视频精简、社交平台画幅调整及编辑软件中的最终修整。

• 从长时间录制中提取精彩片段
• 用拍摄素材制作Vlog
• 为产品演示添加文字和旁白

Work with AI as a coding partner, choosing who writes code and who guides the work. Supports role switching, test generation, ongoing code review, debugging, and step-by-step explanations for learning.

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• Write code with ongoing AI review
• Direct AI implementation while reviewing its output
• Develop features by writing tests first

Work with AI as a coding partner, choosing who writes code and who guides the work. Supports role switching, test generation, ongoing code review, debugging, and step-by-step explanations for learning.

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• Write code with ongoing AI review
• Direct AI implementation while reviewing its output
• Develop features by writing tests first

Learn to examine compiled programs through one interactive lesson per session. Labs and quizzes cover file formats, machine instructions, program behavior, and analysis tools, while recorded observations provide evidence for completing each lesson and resuming later.

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• Learn to read programs you compiled yourself
• Study binary formats and machine instructions
• Check analysis claims against observed output

Analyze Neuropixels neural recordings with SpikeInterface, from loading and preprocessing to motion correction and spike sorting, which separates signals by neuron. Calculate quality metrics, review candidate units, and export plots and data for further inspection.

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• Inspect and preprocess SpikeGLX, Open Ephys, or NWB recordings
• Check and correct movement-related drift before spike sorting
• Evaluate and select units using quality metrics

Review and rewrite prose that feels repetitive, vague, or formulaic while preserving its meaning, evidence, and voice. Get quoted examples of problems, a revised draft, an explanation of edits, and a second review.

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• Polishing an AI-assisted blog draft
• Reviewing documentation for vague wording
• Editing repetitive marketing copy

Review a product or major feature before development starts. Assess demand, revenue, repeat use, trust, and user reach, then identify the riskiest assumption, a small validation step, and work to delay.

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• Check demand and revenue assumptions before building an MVP
• Review positioning before creating a landing page
• Assess adoption risk for a major feature

Create structured Markdown specifications that AI agents can read and use. Organize requirements, constraints, interfaces, acceptance criteria, and testing plans into a self-contained document with clear definitions and examples.

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• Writing specifications for AI-assisted implementation
• Defining requirements and acceptance criteria
• Documenting APIs and data contracts

Use a concise SEO reference to review content credibility, page performance, site structure, and page elements. It explains key checks, structured data types, measurement tools, and editorial practices for AI-assisted content.

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• Learn the main areas to check for SEO
• Review credibility and originality in articles
• Understand page performance metrics and targets

Compare major AI coding tools and consult practical guidance on prompts, project instructions, debugging, workflows, and costs. Use the reference to choose suitable tools and identify why an AI-assisted coding task is stuck.

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• Comparing AI coding tools for a task
• Improving prompts and project instructions
• Troubleshooting stalled AI coding tasks