1.2K skills · sorted by relevance
Turn post-publish notes into pipeline improvements. Use after a video ships, or when the user says "retro", "here is my feedback", or "wrap up this project".
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AI-driven Flutter E2E testing via VM Service CLI. Control running Flutter apps in debug mode for smoke tests, regression checks, exploratory testing, and UI automation. Trigger when user mentions E2E testing, UI automation, smoke tests, integration testing, test automation, controlling Flutter apps, VM Service interaction, debugging UI flows, automated regression testing, CI sanity checks, or testing native dialogs/permissions/WebViews. Supports stateful named instances or stateless direct URI connections. Ideal for rapid test feedback, AI agent workflows, element discovery, screenshot capture, log collection, and scriptable UI interactions (tap, scroll, enterText). Use for troubleshooting flaky tests, automating repetitive manual tests, verifying app behavior after merges, or setting up automated QA pipelines.
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Experimental workflow for configuring an autonomous software delivery factory. Use when choosing feedback sources, schedules, worktree behavior, autonomy gates, or drafting proposed host automations for report-only review.
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Master effective code review practices to provide constructive feedback, catch bugs early, and foster knowledge sharing while maintaining team morale. Use when reviewing pull requests, establishing review standards, or mentoring developers.
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Implement comprehensive evaluation strategies for LLM applications using automated metrics, human feedback, and benchmarking. Use when testing LLM performance, measuring AI application quality, or establishing evaluation frameworks.
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Master effective code review practices to provide constructive feedback, catch bugs early, and foster knowledge sharing while maintaining team morale. Use when reviewing pull requests, establishing...
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Govern FriendlyBet agent values, professional standards, anti-hallucination behavior, truthfulness, risk reporting, AI resource discipline, feedback loops, skill improvement, performance reviews, decision-rights hygiene, and team quality. Use when creating, reviewing, promoting, correcting, or retiring agents; reducing hallucinations or mistakes; reviewing AI/tool usage; handling agent incidents; or aligning work with Eyal's philanthropic user-first approach.
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Senior Kotlin specialist code review — framework-agnostic. Use whenever the user asks to review, audit, critique, or get feedback on Kotlin code, a file, a class, a function, a module, a diff, a branch, a commit, or a pull request. Judges Kotlin language idioms, logic correctness, architecture and layering, concurrency (coroutines, Flow, structured concurrency, cancellation, race conditions), null safety, exception safety, testability, performance, and security. Detects force-unwraps, unchecked casts, GlobalScope, leaked mutability, broken structured concurrency, hidden side effects, weak abstractions, untestable seams, allocation hot spots, weak crypto, input-validation gaps, and PII logging. Outputs prioritized findings with file:line anchors and minimal-diff fixes. No assumptions about DI framework, UI framework, or build system.
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Set up and optimize repositories for AI coding agents. Creates minimal AGENTS.md, CLAUDE.md symlink, docs/REQUIREMENTS.md, docs/BUSINESS-RULES.md, feedback loops, and deterministic enforcement (Claude Code hooks, OpenCode plugins). Use when user wants to make a repo AI-friendly, set up AGENTS.md/CLAUDE.md, document requirements/business rules for AI, add pre-commit hooks for AI workflows, or optimize codebase structure for coding agents.
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Turn owner feedback about agent behavior into concrete system changes. Use when the owner says something is off, wants the assistant to improve how it operates, asks for a reflection, or wants a durable fix instead of a one-off apology.
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Use when working with Coderabbit — codeRabbit AI code review management including automated review comments, auto-suggestions, review customization, and learning from feedback. Use when configuring CodeRabbit for AI-assisted code review, custom review rules, and automated suggestion workflows.
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Use when working with Codescene — codeScene behavioral code analysis including code health scoring, hotspot detection, change coupling analysis, and PR integration for code quality gates. Use when configuring CodeScene for codebase visualization, technical debt prioritization, and automated code review feedback.
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Receive and act on code review feedback with technical rigor, not performative agreement or blind implementation
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Review PR changes against project standards and post feedback
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The 10-second design audit. Look at any design and name what's working and what's not within seconds. Trains rapid pattern recognition for hierarchy, spacing, type, and color. Use when evaluating designs quickly, giving first-impression feedback, or building perception speed.
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Run taste-informed design reviews using Observation > Principle > Question. Use when facilitating design critiques, improving feedback quality on a team, or building a shared vocabulary for quality.
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Write a structured design review that someone can act on without follow-up questions. Use when giving async design feedback, writing portfolio case studies, or documenting design decisions.
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Animation as communication. Feedback, orientation, emphasis, delight. If motion doesn't serve one of these four purposes, it shouldn't exist. Use when evaluating animation quality, designing transitions, or deciding whether motion adds or subtracts.
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Response timing, acknowledgment, and making the interface feel alive. Every action deserves a response at the right speed. Use when designing interactions, evaluating responsiveness, or diagnosing why a product feels sluggish or dead.
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Use when the user just says "plan", "planen" or "roadmap": offer a template via aos-plan-canvas templates. Open plans and HTML artifacts in a local browser canvas where the human annotates elements, chats, and approves or requests changes without leaving the page. Use for planning, whenever a user says "plan", "roadmap", "visualize the plan", "review the plan" or /plan-canvas, right after a brainstorm or grill interview has produced a plan, and whenever any skill's artifact (plan, design, comparison, report, diagram) can be reviewed visually instead of with typed feedback.
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A prototyping skill that generates a local HTML mock with a built-in feedback layer, allowing users to drop visual comments (red dots) for UI fixes.
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Experimental workflow for summarizing work that still needs human judgment across configured pull requests, issues, feedback, errors, and delivery signals. Use for a human decision queue or bounded review.
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Experimental workflow for collecting and triaging product feedback, product telemetry, runtime errors, and issue reports. Use when scanning configured signal sources and applying separate fix, reply, or close rules.
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Experimental workflow for auditing recurring feedback, telemetry, errors, and brittle delivery paths to find systemic fixes. Use for periodic or requested cross-source lookbacks, not routine single-item intake.
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