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Found 1,371 Skills
Cut a release — detect versioning context, generate a changelog from conventional commits, bump versions, and create a git tag. Use when the user says "release", "cut a release", "tag a release", "bump the version", "create a changelog", "ship a version", "publish", or any variation of shipping/publishing a version. This skill is intentionally generic and works across any repo — it infers context from git history and project structure rather than assuming a specific setup.
Expert knowledge for Azure AI Anomaly Detector development including troubleshooting, best practices, architecture & design patterns, limits & quotas, configuration, and deployment. Use when using univariate/multivariate APIs, Docker/IoT Edge containers, predictive maintenance flows, or regional limits, and other Azure AI Anomaly Detector related development tasks. Not for Azure AI Metrics Advisor (use azure-metrics-advisor), Azure Monitor (use azure-monitor), Azure Machine Learning (use azure-machine-learning).
Run Karpathy-style autoresearch optimization on any content. Generates 50+ variants, scores with a 5-expert simulated panel, evolves winners through multiple rounds, outputs optimized version + full experiment log. Use when optimizing landing pages, email sequences, ad copy, headlines, form pages, CTA text, or any conversion-focused content. Triggers on "optimize this page", "run autoresearch", "score these variants", "A/B test this copy".
Apply Partial Least Squares SEM (PLS-SEM) with reflective and formative measurement models to maximize explained variance in endogenous constructs. Use this skill when the user has small samples, formative indicators, or exploratory models, needs to assess AVE/CR/HTMT, or when they ask 'should I use PLS or CB-SEM', 'how do I handle formative constructs', or 'what is the path coefficient significance'.
Use when refactoring code with poor names, when asked to improve naming, or when a user struggles to name a class/method/variable. Symptoms include -Manager/-Util suffixes, single-letter variables, process/handle/do verbs, primitive obsession, god methods with multiple responsibilities.
Grafana OSS core features — dashboards, panels, visualization types, data sources, template variables, alerting, annotations, provisioning, RBAC, service accounts, and configuration. Use when building dashboards, configuring data sources, setting up provisioning YAML, managing users and permissions, writing PromQL/LogQL/TraceQL in panels, or configuring Grafana server settings.
Plan-then-execute implementation against SPEC.md. Native single-thread loop, no sub-agents. On test or build failure, auto-invokes the backprop skill before retrying — a failed verification always considers whether a new §V invariant would prevent recurrence. Triggers when the user asks to build, implement, execute the spec, or tackle a specific §T task (`build §T.3`, `build --next`, `implement next task`, `run the build`). Expects SPEC.md to exist; if not, defers to the spec skill.
Elite frontend image-direction skill for generating premium, artistic, implementation-friendly website design references. Uses combinatorial variation to avoid repetitive AI aesthetics, enforces cinematic hero minimalism, strong hierarchy, generous spacing, image-led composition, and anti-slop visual discipline. For visual frontend tasks, this skill must first generate the design image(s) itself, deeply analyze them, then implement the frontend to match them as closely as possible.
Lee una URL o lista de ClickUp con tareas de implementación de GoHighLevel y ejecuta automáticamente las que sean automatizables vía API/MCP, dejando claras las que requieren implementación manual. Usar cuando el usuario pase un link de ClickUp y diga "ejecutá", "implementá", "auto-implementá", "auto-ejecutá", "corré las tareas en GHL", "hacé esto en GHL", o cuando el output de `ghl-task-builder` (alias `ghl-clickup-task-builder`) ya esté en ClickUp y se quiera dispararlo. Esta skill es complementaria — `ghl-task-builder` GENERA tareas, esta skill las EJECUTA.
Multi-perspective adversarial review. 4 Agents are spawned in parallel (full mode), each identifying issues from different perspectives, and the main thread makes a comprehensive ruling. Trigger methods: /story-review, /审查, "审查一下", "帮我审一下"
Rare disease genomics research -- disease identification via Orphanet, causative gene discovery, gene-disease validity assessment via GenCC, pathogenic variant lookup via ClinVar, HPO phenotype mapping, epidemiology and prevalence data, clinical trial search, and literature review. Use when users ask about rare diseases, orphan diseases, genetic causes of rare conditions, Orphanet codes, HPO phenotypes, gene-disease validity, rare disease prevalence, or treatment options for rare genetic disorders.
Solve Linear Programming (LP), Mixed-Integer Linear Programming (MILP), and Quadratic Programming (QP, beta) with the Python API. Use when the user asks about optimization with linear or quadratic objectives, linear constraints, integer variables, scheduling, resource allocation, facility location, production planning, portfolio optimization, or least squares.