Customer feedback analysis — sentiment detection, NPS/CSAT frameworks, feature request clustering, support ticket triage, churn signal detection, and feedback-to-roadmap translation
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Customer feedback analysis — sentiment detection, NPS/CSAT frameworks, feature request clustering, support ticket triage, churn signal detection, and feedback-to-roadmap translation
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Help users draft and, when authorized, submit feedback to volcengine/volcengine-skills: skill problems, missing capabilities, cloud scenarios, and successful Agent workflows. Use for explicit feedback or sharing requests, or an optional invitation at a natural summary after Volcengine CLI errors or an incompletely solved task. Feedback never blocks the main task.
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Inject juice and game feel into gameplay code using the project's chosen middleware. Use when adding screen shake, tweens, particles, audio feedback, haptics, hitstop, or any form of "juice" to gameplay events. Triggers on requests like "add juice", "make this feel better", "add screen shake", "polish this feature", "add feedback to this action", "make the hit feel impactful", "add particles when", "screen shake on damage", "tween this", "add camera shake", "make this snappy", or any game feel, polish, or feedback work. Always reads ProjectConfig.yaml -> feel_tools and docs/GFD.md Feedback Matrix before generating code.
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Deliver feedback using Kim Scott's Radical Candor framework - care personally while challenging directly. Use when a leader needs to give difficult feedback, says "I need to tell someone something hard", "how do I give feedback without hurting them", "I've been avoiding a conversation", "my direct report isn't performing", "someone on my team has a blind spot", "I keep sugarcoating things", or "how do I be honest without being a jerk". Also trigger when someone describes being too nice (ruinous empathy) or too harsh (obnoxious aggression), or when they describe avoiding a conversation they know they need to have.
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Navigate difficult conversations and deliver constructive feedback using structured frameworks. Covers the Preparation-Delivery-Follow-up model and Situation-Behavior-Impact (SBI) feedback technique. Use when preparing for difficult conversations, giving feedback, or managing conflicts.
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Identifies when task outputs require iteration based on quality signals, unmet requirements, or explicit feedback. Triggers appropriate re-execution strategies. Activate on 'needs iteration', 'retry needed', 'not good enough', 'try again', 'refine output'. NOT for feedback generation (use dag-feedback-synthesizer) or convergence tracking (use dag-convergence-monitor).
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Address GitHub PR review comments at line, file, and PR level by fetching, evaluating, fixing, committing, and resolving feedback. Use when invoked as `$pr-resolve-review-feedback` or when the user asks to resolve PR feedback.
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Identifies when task outputs require iteration based on quality signals, unmet requirements, or explicit feedback. Triggers appropriate re-execution strategies. Activate on 'needs iteration', 'retry needed', 'not good enough', 'try again', 'refine output'. NOT for feedback generation (use dag-feedback-synthesizer) or convergence tracking (use dag-convergence-monitor).
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Act on user feedback attached to the current session. Use when the user submits feedback on the session's changes via the Submit Feedback button.
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为人工测试OpenClaw候选版本准备隔离的OCM副本或经批准的现有Gateway环境,指导测试、整理反馈,并协助在公开报告前检查内容。
将代码审查意见与实际代码、支持的运行环境及现有行为进行核对,确认建议是否合理,梳理疑问并依据技术证据回复,再逐项修改和测试。
Generate several AI design options, view them on a comparison board, and collect organized feedback. Use the results to explore visual directions and refine designs when a feature’s appearance is undecided or an existing interface needs improvement.
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Check earlier Paperclip tasks for verified progress and actual deliverables, then report findings with links. When requested, add feedback as the connected person, with safeguards against posting the same comment twice.
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Explore recommended papers in Paperzilla projects, search project feeds, and summarize available paper text. The skill also helps explain research relevance, record recommendation feedback, export records as JSON, and retrieve personal feed URLs.
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Design and implement interface responses such as button feedback, loading indicators, page transitions, and swipe gestures. Use motion to communicate actions and state changes, with guidance on timing, performance, and support for people who prefer reduced animation.
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Review code changes through a structured check of requirements, design, correctness, security, performance, and tests. Produce specific, constructive feedback that separates required fixes from optional suggestions, and build shared review guidelines for a development team.
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Organize human review in Arize by defining label choices, numeric ranges, or free-text feedback fields. Manage review queues and reviewers, submit annotations for individual records, and apply existing labels to project spans, or individual processing records, in bulk.
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Explore training workflows that reduce harmful model responses using a written set of principles. The skill covers self-critique, revised training examples, and RLAIF, reinforcement learning from AI feedback, with implementation examples and hardware guidance.
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Prepare self-assessments, manager reviews, and documents for meetings that align employee ratings. Structure achievements, goal evidence, development plans, and promotion cases, turning vague feedback into specific observations about behavior and impact.
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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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Review a Figma design, screenshot, or written description for usability, visual hierarchy, consistency, and accessibility. Receive specific findings, explanations, and prioritized improvements, with feedback tailored to the design stage and intended users.
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Analyze meeting transcripts to understand speaking share, verbal habits, listening, and facilitation. Receive feedback grounded in specific quotes, practical suggestions for future meetings, and comparisons across periods when enough meeting data is available.
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Run a structured sprint retrospective, a review of a short work cycle, using team feedback and delivery results. Identify shared themes and produce two or three prioritized improvements with owners, deadlines, and measures of success.
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Monitor an open GitHub pull request over time, respond to review feedback, and address automated check failures. Apply and push fixes, then report whether it appears ready to merge or what still blocks progress.
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