1.2K skills · sorted by relevance
Prepare a user-reviewed Arch Studio bug report or feature request for GitHub. Use when the user runs /as:studio-feedback, says "report a bug", "this skill broke", "send feedback", or requests a feature. Do not use for Claude Code's native /feedback command.
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Design of active analog circuits built around operational amplifiers and discrete gain stages — inverting, non-inverting, difference, and instrumentation topologies, negative feedback and loop stability (gain-bandwidth product, phase margin, compensation), active filters (Sallen-Key, multiple-feedback biquad), sinusoidal and relaxation oscillators, comparators and Schmitt triggers, voltage references (bandgap, shunt, series), and linear versus switching voltage regulators. Covers how to pick a topology, close a feedback loop that stays stable, set gain and bandwidth, and choose a power-conversion approach. Use when designing an amplifier, filter, oscillator, reference, comparator, or regulator, or when reasoning about feedback stability, loop gain, phase margin, or op-amp non-idealities.
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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-agent-toolkit: 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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Prepare an OpenClaw release candidate for human testing using an isolated OCM copy or an approved existing Gateway. Guide testing, organize feedback, and prepare reports for review while the tester operates interactive features and judges quality.
Evaluate code review feedback against the actual code, supported environments, and existing behavior. Clarify uncertain requests, respond with technical evidence, and implement valid changes one at a time with tests for each fix.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.