deep-research
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deepwiki
Query DeepWiki for repository documentation and structure. Use to understand open source projects, find API docs, and explore codebases.
exhaustive-systems-analysis
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aesthetic-guide
Research a UI design aesthetic and produce exhaustive, implementation-ready design guidelines for coding agents. Use when the user names an aesthetic (brutalist, glassmorphism, retro-futuristic, Swiss modernist, Apple HIG, neumorphism, minimalism, cyberpunk, Material Design, art deco, vaporwave, etc.) and wants a complete style guide with exact CSS values, color palettes, component states, animations, and typography — detailed enough for a coding agent to faithfully implement the aesthetic with zero ambiguity.
agent-changelog
Compile an agent-optimized changelog by cross-referencing git history with plans and documentation. Use when asked to "update changelog", "compile history", "document project evolution", or proactively after major milestones, architectural changes, or when stale/deprecated information is detected that could confuse coding agents.
agent-telemetry
Make application behavior visible to coding agents by exposing structured logs and telemetry. Use when asked to "add telemetry", "make logs accessible to agents", "add observability", "debug with logs", or when an agent needs to understand runtime behavior but has no way to query logs. Also use when debugging is difficult because there are no structured logs, when agent docs (CLAUDE.md, AGENTS.md) lack instructions for querying application logs, or when setting up logging infrastructure for a new or existing web application.
agentic-docs
Write clear, plain-spoken code comments and documentation that lives alongside the code. Use when writing or reviewing code that needs inline documentation like file headers, function docs, architectural decisions, or explanatory comments. Works well for both human readers and AI coding assistants who see one file at a time.
architectural-refactor
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architecture-scaffold
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autonomous-agent-readiness
Assess a codebase's readiness for autonomous agent development and provide tailored recommendations. Use when asked to evaluate how well a project supports unattended agent execution, assess development practices for agent autonomy, audit infrastructure for agent reliability, or improve a codebase for autonomous agent workflows. Triggers on requests like "assess this project for agent readiness", "how autonomous-ready is this codebase", "evaluate agent infrastructure", or "improve development practices for agents".
blog-drafter
Interview-driven blog post drafting for technical product audiences. Use when user wants to write a blog post, article, or essay and needs help developing their thesis, structure, and initial draft. Triggers on "write a blog post", "draft an article", "help me write about X", "blog drafter", or when user has a topic they want to turn into written content. Conducts structured interviews using AskUserQuestion to extract the user's unique insights before generating drafts.
capture-learning
Analyze recent conversation context and capture learnings to project knowledge files (for project-specific insights) or skills/commands/subagents (for cross-project patterns). Use when the user asks to "capture this learning", "update the docs with this", "remember this for next time", "document this issue", "add this to CLAUDE.md", "save this knowledge", or "update project knowledge". Also triggers after resolving build/setup issues, discovering non-obvious patterns, or completing debugging sessions with valuable insights.
checkpoint
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codebase-study-guide
Generate a pedagogically-grounded study guide for learning an unfamiliar codebase. Use when the user wants to onboard onto a codebase, understand a project's architecture, create learning materials for a team, or asks things like \"help me learn this codebase\", \"create an onboarding guide\", \"I'm new to this project\", \"how does this system work\", \"study guide for this repo\", or \"explain this codebase to me\". Produces a structured document that builds understanding from purpose to systems to patterns, using evidence-based learning techniques (elaborative interrogation, concept mapping, threshold concepts, worked examples, progressive disclosure).
data-sleuth
Identify non-obvious signals, hidden patterns, and clever correlations in datasets using investigative data analysis techniques. Use when analyzing social media exports, user data, behavioral datasets, or any structured data where deeper insights are desired. Pairs with personality-profiler for enhanced signal extraction. Triggers on requests like "what patterns do you see", "find hidden signals", "correlate these datasets", "what am I missing in this data", "analyze across datasets", "find non-obvious insights", or when users want to go beyond surface-level analysis. Also use proactively when you notice interesting anomalies or correlations during any data analysis task.
de-slop
Remove LLM-isms and AI writing patterns from text. This skill should be used when editing prose to sound less like AI output — removing overused words, fixing structural tells, and restoring natural human voice. Triggers: \"de-slop\", \"remove AI writing\", \"humanize this\", \"sounds too AI\", \"LLM-isms\", \"AI slop\", or when reviewing text that reads like chatbot output.
dead-code-sweep
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deep-research
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deep-work
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docs-changelog
Write changelog entries for open source documentation sites using Keep a Changelog format. Use when asked to "write a changelog", "update the changelog", "add changelog entry", "document recent changes", or after a release/set of changes that should be recorded. Reviews git commits since the last changelog entry and produces a categorized, human-readable entry.
exhaustive-systems-analysis
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explainer-visuals
Create high-quality animated explainer visuals for essays and blog posts. Use when the user wants to visualize concepts, processes, data, or ideas with interactive web animations. Triggers on requests like "create a visual for", "animate this concept", "make an explainer", "visualize this idea", "diagram this process", "show this data", or when essay content would benefit from visual explanation. Handles abstract concepts (mental models, frameworks), technical processes (algorithms, systems), and data visualization (trends, comparisons). Outputs self-contained HTML/CSS/JS that embeds directly in web content.
explanatory-playground
Build interactive debugging interfaces that reveal internal system behavior. Use when asked to "help me understand how this works", "show me what's happening", "visualize the state", "build a debug view", "I can't see what's going on", or any request to make opaque system behavior visible. Applies to state machines, data flow, event systems, algorithms, render cycles, animations, CSS calculations, or any mechanism with hidden internals.
fixer
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formal-verify
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handoff
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hierarchical-matching-systems
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interaction-design
Design intuitive, meaningful interactions grounded in user goals and cognitive principles. Use when designing component behaviors, user flows, feedback systems, error handling, loading states, transitions, accessibility, keyboard navigation, touch/gesture interactions, or when evaluating interaction quality. Also use for modal vs modeless decisions, direct manipulation patterns, input device considerations, emotional/dramatic aspects of UX, or when asked about making interfaces feel responsive, humane, and goal-directed.
interactive-study-guide
Transform a codebase study guide into a polished interactive web experience. This skill should be used when the user has a completed study guide markdown file (from codebase-study-guide or similar) and wants to turn it into an interactive pedagogical app. Triggers on requests like \"make this study guide interactive\", \"turn this into an interactive experience\", \"visualize this study guide\", \"create an interactive version\", or when a user has a study guide .md file and wants a richer presentation. Produces a Vite-served single-page app with scroll-driven storytelling, interactive architecture diagrams, animated code walkthroughs, and progressive disclosure.
literate-guide
Create a narrative guide to a codebase or feature in the style of Knuth's Literate Programming — code and prose interwoven as a single essay, ordered for human understanding rather than compiler needs. Use when the user asks to 'explain this codebase as a story', 'write a literate guide', 'create a narrative walkthrough', 'tell the story of this code', 'Knuth-style documentation', 'weave a guide for this feature', or when they want deep, readable documentation that treats the program as literature. Also trigger when someone wants a document that a thoughtful reader could follow from start to finish and come away understanding both WHAT the code does and WHY every design choice was made.
macos-app-design
Use when designing or building native macOS applications with SwiftUI or AppKit. Triggers on menu bar structure, keyboard shortcuts, multi-window behavior, Liquid Glass design system, macOS Tahoe/Sequoia, sidebar navigation, toolbar design, app icons, SF Symbols, or making an app feel like a "good Mac citizen."
manual-testing
Guide users step-by-step through manually testing whatever is currently being worked on. Use when asked to "test this", "verify it works", "let's test", "manual testing", "QA this", "check if it works", or after implementing a feature that needs verification before proceeding.
model-first-reasoning
Apply Model-First Reasoning (MFR) to code generation tasks. Use when the user requests "model-first", "MFR", "formal modeling before coding", "model then implement", or when tasks involve complex logic, state machines, constraint systems, or any implementation requiring formal correctness guarantees. Enforces strict separation between modeling and implementation phases.
multi-model-meta-analysis
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openclaw-customizer
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optimize-agent-docs
Build a retrieval-optimized knowledge layer over agent documentation in dotfiles (.claude, .codex, .cursor, .aider). Use when asked to "optimize docs", "improve agent knowledge", "make docs more efficient", or when documentation has accumulated and retrieval feels inefficient. Generates a manifest mapping task-contexts to knowledge chunks, optimizes information density, and creates compiled artifacts for efficient agent consumption.
posthog-analytics
Product analytics expert using PostHog MCP. Triggers on requests to understand user behavior, surface insights, create dashboards, analyze funnels, track metrics, set up experiments, or answer questions about product performance. Use when working with PostHog data, discussing analytics strategy, investigating user journeys, retention, conversion, feature adoption, or when asked to help understand what's happening in the product.
process-hunter
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proposal-review
Facilitate methodical review of proposals (technical designs, product specs, feature requests). Use when asked to "review this proposal", "give feedback on this doc", "help me review this RFC", or when presented with a document that needs structured feedback. Handles markdown files, GitHub gists/issues/PRs, and other text formats. Chunks proposals intelligently, predicts reviewer reactions, and produces feedback adapted to the proposal's format.
record-todos
Enter todo recording mode to capture ideas without acting on them. Use when the user says "record todos", "let's capture some todos", "brainstorm mode", or wants to dump ideas without immediate execution. Captures thoughts to .claude/todos/, then organizes and prioritizes on exit.
research-prompt
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review-package
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rust
Robust Rust patterns for file-backed data, parsing, persistence, FFI boundaries, and system integration. Use when writing Rust that handles file formats, subprocess integration, PID/process management, Serde serialization, or UniFFI boundaries. Covers UTF-8 safety, atomic writes, state machines, and defensive error handling.
seam-ripper
Ruthlessly analyze architectural seams—the interfaces, boundaries, and contracts between system components—to expose coupling problems, abstraction leaks, and design failures. Use when asked to review architecture, analyze coupling, find interface problems, improve module boundaries, audit dependencies, or redesign system structure. Produces uncompromising redesign proposals that prioritize correctness over backwards compatibility.
simplicity-audit
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tuning-panel
Create visual parameter tuning panels for iterative adjustment of animations, layouts, colors, typography, physics, or any numeric/visual values. Use when the user asks to "create a tuning panel", "add parameter controls", "build a debug panel", "tweak parameters visually", "fine-tune values", "dial in the settings", or "adjust parameters interactively". Also triggers on mentions of "leva", "dat.GUI", or "tweakpane".
typography
Apply professional typography principles to create readable, hierarchical, and aesthetically refined interfaces. Use when setting type scales, choosing fonts, adjusting spacing, designing text-heavy layouts, implementing dark mode typography, or when asked about readability, font pairing, line height, measure, typographic hierarchy, variable fonts, font loading, or OpenType features.
unix-macos-engineer
Expert Unix and macOS systems engineer for shell scripting, system administration, command-line tools, launchd, Homebrew, networking, and low-level system tasks. Use when the user asks about Unix commands, shell scripts, macOS system configuration, process management, or troubleshooting system issues.
pr-screenshot-comparison
Create clear, polished before-and-after screenshots for a GitHub pull request. Use when a UI change needs visual proof: capture matching states, crop to the relevant UI, stitch and caption one comparison image, attach it natively to the PR, and keep the image out of the repository.
architecture-exploration
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