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Agent skills

Skills you can use with AI coding agents, indexed from public GitHub repositories.

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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.
petekp/agent-skills 3
architectural-refactor Execute architectural refactoring from an assessment document with deterministic, chunked operations and aggressive verification at every step. Use when you have an architectural assessment, clean architecture review, refactoring recommendations, or seam-ripper output and need to actually perform the refactoring safely. Also use when asked to "refactor based on this assessment", "execute these architectural recommendations", "fix architectural drift", "refactor in chunks", or any request to systematically restructure a codebase according to a plan. Designed specifically to prevent the kind of agent drift that causes architectural problems in the first place.
petekp/agent-skills 3
research-prompt Craft a high-quality prompt for a deep research agent (like ChatGPT Deep Research) through adaptive interviewing. Use when the user wants to research something but needs help formulating what to ask — when they say "I need to research X", "help me figure out what to ask about Y", "write a research prompt for Z", "I want to use deep research on...", or when they have a vague research need and want a precise, comprehensive prompt that will get excellent results from a research agent. Also use when the user mentions deep research, ChatGPT research, or preparing a query for an AI research tool.
petekp/agent-skills 3
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.
petekp/agent-skills 3
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.
petekp/agent-skills 3
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.
petekp/agent-skills 3
handoff Generate a smart bootstrap prompt to continue the current conversation in a fresh session. Use when (1) approaching context limits, (2) user says "handoff", "bootstrap", "continue later", "save session", or similar, (3) before closing a session with unfinished work, (4) user wants to resume in a different environment. Outputs a clipboard-ready prompt capturing essential context while minimizing tokens.
petekp/agent-skills 3
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.
petekp/agent-skills 3
simplicity-audit First-principles simplification analysis for codebases. Methodically inventories what a codebase actually does, then asks whether each piece of complexity earns its keep. Use when asked to "simplify this codebase", "is this overengineered", "how could this be simpler", "reduce complexity", "first principles review", "essential complexity audit", "do we really need all this", or any request to rethink whether the current implementation is the simplest way to achieve its goals. Also useful when a codebase feels harder to work with than it should, when onboarding takes too long, or when changes that seem simple keep ballooning in scope.
petekp/agent-skills 3
checkpoint Meta-cognitive decision support that analyzes current context and surfaces intelligent next-step options to the user. Use this skill when: (1) User explicitly invokes /checkpoint, (2) Significant work has been completed and a checkpoint is valuable, (3) Uncertainty or ambiguity exists about requirements or approach, (4) Task complexity has expanded beyond initial scope, (5) Before finalizing or committing to ensure nothing is missed. This skill pauses execution, assesses the situation holistically, and presents 2-5 contextually-appropriate options via AskUserQuestion, with a recommended option and rationale.
petekp/agent-skills 3
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.
petekp/agent-skills 3
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.
petekp/agent-skills 3
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.
petekp/agent-skills 3
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.
petekp/agent-skills 3
Debug Cluster Provides systematic debugging approaches for HyperShift hosted-cluster issues. Auto-applies when debugging cluster problems, investigating stuck deletions, or troubleshooting control plane issues.
openshift/hypershift 515
Code Formatting MANDATORY: When writing Go tests, you MUST use 'When...it should...' format for ALL test names. When writing any Go code, you MUST remind user to run 'make lint-fix' and 'make verify'. These are non-negotiable HyperShift requirements.
openshift/hypershift 515
Konflux Archived PipelineRuns Accesses archived Konflux PipelineRuns, TaskRuns, and pod logs via KubeArchive. Auto-applies when checking Konflux PipelineRun results, investigating enterprise contract failures, or retrieving logs from completed Konflux CI runs.
openshift/hypershift 515
Git Commit Format Apply HyperShift conventional commit formatting rules. Use when generating commit messages or creating commits.
openshift/hypershift 515
Effective Go Apply Go best practices, idioms, and conventions from golang.org/doc/effective_go. Use when writing, reviewing, or refactoring Go code to ensure idiomatic, clean, and efficient implementations.
openshift/hypershift 515
Create HC AWS Create a HyperShift HostedCluster on AWS for development and testing, with optional custom CPO/HO images.
openshift/hypershift 515
Install HO AWS Install HyperShift Operator with private AWS and external-dns settings.
openshift/hypershift 515
E2E Test Runner Provides the ability to run and iterate on HyperShift e2e tests. Auto-applies when implementing features that require e2e validation, fixing e2e test failures, or working on tasks that need live cluster testing.
openshift/hypershift 515
Build HO Image Build and push hypershift-operator container image. Auto-applies when testing HO changes that require deploying to a live cluster.
openshift/hypershift 515
Build CPO Image Build and push control-plane-operator container image. Auto-applies when testing CPO changes that require deploying to a live cluster.
openshift/hypershift 515