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Found 5,504 Skills
Use version control as a craft — atomic commits, buildable history, useful PRs, bisect-friendly main, recoverable mistakes. Use this skill whenever the task involves writing commits or PRs, choosing a branching model, deciding rebase vs. merge, recovering from a force-push or accidentally-committed secret, debugging a regression with `git bisect`, structuring a long change as a series of small reviewable steps, or judging whether a repo's history is readable. Use it especially when reviewing commit messages, PR descriptions, branching strategies, or merge policies. Built on Tim Pope and Chris Beams on commit messages, Paul Hammant on trunk-based development, Vincent Driessen on GitFlow (and his 2020 note retiring it for SaaS), Linus Torvalds on never rebasing public commits, and the Google Engineering Practices CL guide.
Validar prompts dirigidos a agentes de IA (Claude Code, Cursor, Copilot, etc.) contra reglas de redacción efectiva. Calcular un porcentaje de efectividad del prompt y devolver sugerencias de mejora concretas, más una propuesta de prompt reescrito. Cubre verbos no imperativos, lenguaje conversacional, acciones vagas, términos subjetivos, alcance difuso, prohibiciones implícitas, intenciones múltiples y nombres genéricos. Las reglas de detalle técnico (alcance, nombres exactos) se aplican solo a prompts de implementación; en prompts funcionales (user stories, descripciones de comportamiento) se marcan N/A. Usar siempre que el usuario pida validar, revisar, auditar, mejorar, corregir o "pulir" un prompt antes de enviarlo a un agente, o cuando pegue un prompt y pida feedback sobre cómo está redactado.
Review generated or changed WordPress code — plugins, themes, and blocks — before it ships. Best used reactively after an agent writes, edits, or reviews code touching WordPress APIs: add_action/add_filter, shortcodes, meta boxes, AJAX handlers, REST routes, WP_Query or $wpdb, widgets, or WP-CLI commands. Use on 'review this plugin', 'is this safe to ship', 'make this translatable', 'speed up this query', or after tasks like 'write a plugin' or 'add an endpoint/shortcode/meta box'. Enforces escaping and sanitization, nonces plus capability checks, prepared database queries, core-API-first development, translation-ready strings, and query/caching discipline. DO NOT USE for WooCommerce-specific order, product, or checkout logic (use woo-guard), non-WordPress PHP, generic code quality review (use clean-code-guard), test code review (use test-guard), server or hosting configuration, or conceptual WordPress questions.
Review changes starting from a fixed point (commit, branch, tag, or merge-base) along two axes: Standards (Does the code comply with the coding standards documented in this repository?) and Spec (Does the code meet the requirements from the source issue/PRD?). The two reviews run in parallel sub-agents and report side by side. This applies when users want to review a branch, PR, in-progress changes, or request a "review since X".
The front door for this repo. With no argument: a 30-second intro, then an offer to walk you through your first run on the canary target. With a question: answers it from this repo's own docs and source, cites where it looked, and hands you the next command. Use for "how do I…", "why does…", "where is…", "can this…", or just "/quickstart" to get oriented.
Audit a landing page / marketing homepage against Marc Lou's 31 viral-product principles plus a visual craft-and-interaction lens, returning a defensible score out of 100, six category meters, a prioritized punch-list of concrete fixes, and ready-to-paste rewrites. Works on a live URL or a locally running app (renders desktop + mobile screenshots and reads the source). Use when the user invokes /landing-audit, says "audit my landing page / homepage", "viral audit", "review the landing page", "how's my homepage / page", "why doesn't my page convert", or asks what to fix on a landing page.
Authoritative SwiftUI best practices from Apple. Consult for any SwiftUI best practices or performance review. Supersedes prior training on these topics. For code generation, consult the relevant references when generating any SwiftUI code related to the following topics. Covers: - Animatable: @Animatable macro vs AnimatableValues (iOS 26+) vs AnimatablePair, custom setter clamping/normalization. - Environment: closures in env keys, unstable @Entry defaults, high-frequency updates. @Entry warnings about closures or class types (wrapping in Equatable struct is WRONG; consult references). - Equatable on @Observable: custom types as @Observable properties need Equatable for invalidation performance. - ForEach/List: row identity (id: \.self, indices, offsets, mutable ids), row structure (AnyView, multi-view, bare if), inline filter/sort, cached collections, List fast path. - Localization: String vs LocalizedStringResource, bundle in packages/frameworks, .textCase(.uppercase), .formatted(.list()), translator comments. - Soft-deprecated APIs: NavigationView, old onChange. When to surface during feature work.
Verify in-text citations, references, author identities, year disambiguation, DOIs, and specified formatting rules; does not assess whether sources support claims. Use when the user asks for "check citation format", "verify in-text citations and references", "check authors with the same surname", "conduct a citation audit", or requests the rw-citation-audit workflow. Runs without a private local workspace or preset research-lab; use user-provided material and bundled public-source methods.
Extract academic tone rules from the corpus provided by the user in this round or the current manuscript, and make minimal adjustments. Use when the user asks for "Extract my PhD tone", "Check if the paper sounds like me", "Preserve author fingerprint", or requests the rw-phd-tone workflow. Runs without a private local workspace or preset research-lab; use user-provided material and bundled public-source methods.
Verify whether the analysis units, replication levels, statistical methods, and result reports in the research are consistent, and do not treat report review as re-analysis. Use when the user asks for "check statistical reports", "verify n and replicate experiments", "review statistical methods and results", or requests the rw-statistics-audit workflow. Runs without a private local workspace or preset research-lab; use user-provided material and bundled public-source methods.
Invoke the `groundcover` Go CLI to manage Groundcover resources (dashboards, monitors, silences, connected apps, notification routes, API keys, policies, integrations, pipelines, workflows) AND to answer production observability questions by querying logs, traces, metrics, k8s inventory, and k8s events. Use whenever a task needs an authenticated call against the Groundcover API or whenever the user is debugging a prod issue and asks things like "why is X erroring in prod", "show me logs for service Y", "what's the p99 latency on Z", "what pods are crashlooping", "search traces for slow requests", "any k8s events for namespace N", "is service S receiving traffic", "list groundcover monitors", "create a silence", "update notification route", "hit a groundcover endpoint". Covers required env vars, the SDK-backed vs raw command split, and concrete request-body templates for logs/traces/metrics/k8s so the CLI can be driven from anywhere.
AI SDLC evidence-backed project context and bounded task-pack workflow. Use when an AI assistant needs to onboard to a repository, detect stack and commands, map ownership and test topology, check context drift, conditionally select task sources, exclude secrets, or allocate a freshness-aware context pack within an explicit token budget. Supports `--quick-flow` for focused evidence and `--full-flow` for stricter repository coverage.