obsidian-facet-selection
Selecciona una faceta de trabajo segun la peticion y registra la decision con fuentes.
obsidian-frontmatter
Aplicar reglas consistentes de YAML frontmatter en Obsidian: un bloque, claves estándar, fechas YYYY-MM-DD, tags en lista, comillas cuando proceda.
obsidian-links
Crear, validar y reparar wikilinks de Obsidian (links internos, enlaces a secciones, anclas ^bloque). Incluye verificación de existencia.
obsidian-markdown-structure
Estandarizar estructura Markdown en Obsidian sin romper Dataview/Templater ni tablas: headings, listas, bloques de código, separadores.
obsidian-mermaid
Crear diagramas Mermaid compatibles con Obsidian (flowchart, sequence, gantt). Evita errores comunes y produce diagramas simples y mantenibles.
obsidian-rag-ops
Ejecuta flujos RAG en Obsidian para responder, resumir, reorganizar o crear notas nuevas con citas trazables.
obsidian-reading-guardrails
Garantiza lectura real, control de limites, registro en cache y validacion de citas/wikilinks en Obsidian.
obsidian-recurring-expenses
Identifica y registra gastos recurrentes desde correos y adjuntos con validacion estricta y trazabilidad.
obsidian-safe-changes
Cambios seguros en archivos del vault: mover, renombrar, editar o eliminar con trazabilidad y recuperacion.
obsidian-session-close
Cierra una sesion dejando resumen, pendientes y mejoras con trazabilidad.
obsidian-sop-authoring
Crear y mantener procedimientos como skills (SKILL.md) con objetivo, cuando usar, pasos y checklist.
obsidian-style-profile
Analiza el estilo de escritura del usuario y genera un perfil con metricas y ejemplos citados.
obsidian-task-ops
Gestionar tareas en notas Markdown de Obsidian (captura, inbox, priorización, daily/weekly). Respeta el formato existente de tasks.
obsidian-vault-ops
Operaciones seguras sobre un vault de Obsidian: buscar, leer, escribir, mover y validar sin romper enlaces. Incluye patrones para evitar alucinaciones.
dhh-writing
This skill should be used when writing in the distinctive style of David Heinemeier Hansson (DHH). It applies when creating blog posts, technical articles, business content, manifestos, or any prose requiring a clear, punchy, opinionated style.
every-style-editor
This skill should be used when reviewing or editing copy to ensure adherence to Every's style guide. It provides a systematic line-by-line review process for grammar, punctuation, mechanics, and style guide compliance.
pragmatic-writing
This skill should be used when writing technical content in the style of Hunt/Thomas (The Pragmatic Programmer) and Joel Spolsky (Joel on Software). It applies when creating technical essays, documentation, tutorials, or explanatory content that needs to be clear, engaging, and actionable.
voice-capture
This skill should be used when extracting voice profiles from sample text, creating voice documentation, or matching a specific writing style. It applies when users provide sample text and want to capture the voice for future use.
writing-orchestration
This skill should be used when orchestrating complex writing workflows with multiple phases. It provides two-agent orchestration patterns, the two-gate content readiness assessment, 10 baseline writing strategies, 20+ situational strategies, and quality checkpoints. Inspired by the Spiral Writing System.
app-creator
Orchestrate iOS/macOS app scaffolding and optional skill adoption for existing projects. Use when users want a guided wizard that can scaffold with XcodeGen and optionally install xcode-makefiles and simple-tasks.
simple-tasks
Install a fast local task workflow for single-project planning with `scripts/task.sh` (claim, done, status, reporting) backed by `tasks/TASKS.md` and optional `tasks/details/` notes. Use for lightweight in-progress task coordination, not full team issue tracking.
xcode-makefiles
Install strict Xcode Makefile tooling for iOS/macOS projects, including build/run/test scripts with AGENT_NAME-based per-agent isolation under build/. Use when a project needs reproducible local CLI builds without full app scaffolding.
ragsharp-build-code-graph
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ragsharp-mcp-code-graph
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ragsharp-query-code-graph
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ammon
What time is it for Ammon? Looks up the current time in Denmark (Europe/Copenhagen timezone) and reports it.
gen-image
Analyze content and generate illustrations via Gemini image API
gist-image
Use when you need to host images (screenshots, diagrams, PNGs) on GitHub for use in PR descriptions, issues, or markdown docs. Solves the problem that `gh gist create` rejects binary files.
image-explore
Brainstorm multiple visual directions for a blog image, generate them in parallel, build a comparison page, and optionally publish as a shareable link (Surge.sh or gist).
showboat
Create executable demo documents with screenshots using Showboat + Rodney. Use when the user wants to document an app, create a visual walkthrough, take screenshots of a deployed site, run an accessibility audit, or build self-verifying documentation.
up-to-date
Sync git repository with upstream. Use at the start of a session, when asked to sync, get up to date, check git status, or when working on a stale branch. Checks branch status, uncommitted changes, PR state, and upstream drift, then takes appropriate actions.
whisper-lolo-audio-ingest
Build or modify the browser-side recording and upload pipeline for whisper-lolo. Use when implementing MediaRecorder + IndexedDB chunking, assembling audio blobs, or configuring Vercel Blob client uploads with progress and callbacks.
whisper-lolo-roadmap
Guide development of the whisper-lolo project based on specifications-projet.md. Use when planning or executing a sprint/PR, validating scope or constraints, or aligning architecture, statuses, and DoD for the Next.js + Vercel + Blob + Inngest + Whisper stack.
whisper-lolo-transcription-jobs
Implement or adjust background transcription jobs for whisper-lolo. Use when wiring Inngest events, handling long-running jobs, chunking before transcription, persisting transcripts, or maintaining the TranscriptionProvider abstraction.
exa-search
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scvi-tools
This skill should be used when working with single-cell omics data analysis using scvi-tools, including scRNA-seq, scATAC-seq, CITE-seq, spatial transcriptomics, and other single-cell modalities. Use this skill for probabilistic modeling, batch correction, dimensionality reduction, differential expression, cell type annotation, multimodal integration, and spatial analysis tasks.
seaborn
Statistical visualization. Scatter, box, violin, heatmaps, pair plots, regression, correlation matrices, KDE, faceted plots, for exploratory analysis and publication figures.
shap
Model interpretability and explainability using SHAP (SHapley Additive exPlanations). Use this skill when explaining machine learning model predictions, computing feature importance, generating SHAP plots (waterfall, beeswarm, bar, scatter, force, heatmap), debugging models, analyzing model bias or fairness, comparing models, or implementing explainable AI. Works with tree-based models (XGBoost, LightGBM, Random Forest), deep learning (TensorFlow, PyTorch), linear models, and any black-box model.
simpy
Process-based discrete-event simulation framework in Python. Use this skill when building simulations of systems with processes, queues, resources, and time-based events such as manufacturing systems, service operations, network traffic, logistics, or any system where entities interact with shared resources over time.
stable-baselines3
Use this skill for reinforcement learning tasks including training RL agents (PPO, SAC, DQN, TD3, DDPG, A2C, etc.), creating custom Gym environments, implementing callbacks for monitoring and control, using vectorized environments for parallel training, and integrating with deep RL workflows. This skill should be used when users request RL algorithm implementation, agent training, environment design, or RL experimentation.
statistical-analysis
Statistical analysis toolkit. Hypothesis tests (t-test, ANOVA, chi-square), regression, correlation, Bayesian stats, power analysis, assumption checks, APA reporting, for academic research.
statsmodels
Statistical modeling toolkit. OLS, GLM, logistic, ARIMA, time series, hypothesis tests, diagnostics, AIC/BIC, for rigorous statistical inference and econometric analysis.
string-database
Query STRING API for protein-protein interactions (59M proteins, 20B interactions). Network analysis, GO/KEGG enrichment, interaction discovery, 5000+ species, for systems biology.
sympy
Use this skill when working with symbolic mathematics in Python. This skill should be used for symbolic computation tasks including solving equations algebraically, performing calculus operations (derivatives, integrals, limits), manipulating algebraic expressions, working with matrices symbolically, physics calculations, number theory problems, geometry computations, and generating executable code from mathematical expressions. Apply this skill when the user needs exact symbolic results rather than numerical approximations, or when working with mathematical formulas that contain variables and parameters.
torch-geometric
Graph Neural Networks (PyG). Node/graph classification, link prediction, GCN, GAT, GraphSAGE, heterogeneous graphs, molecular property prediction, for geometric deep learning.
torchdrug
Graph-based drug discovery toolkit. Molecular property prediction (ADMET), protein modeling, knowledge graph reasoning, molecular generation, retrosynthesis, GNNs (GIN, GAT, SchNet), 40+ datasets, for PyTorch-based ML on molecules, proteins, and biomedical graphs.
transformers
This skill should be used when working with pre-trained transformer models for natural language processing, computer vision, audio, or multimodal tasks. Use for text generation, classification, question answering, translation, summarization, image classification, object detection, speech recognition, and fine-tuning models on custom datasets.
treatment-plans
Generate concise (3-4 page), focused medical treatment plans in LaTeX/PDF format for all clinical specialties. Supports general medical treatment, rehabilitation therapy, mental health care, chronic disease management, perioperative care, and pain management. Includes SMART goal frameworks, evidence-based interventions with minimal text citations, regulatory compliance (HIPAA), and professional formatting. Prioritizes brevity and clinical actionability.
umap-learn
UMAP dimensionality reduction. Fast nonlinear manifold learning for 2D/3D visualization, clustering preprocessing (HDBSCAN), supervised/parametric UMAP, for high-dimensional data.
uniprot-database
Direct REST API access to UniProt. Protein searches, FASTA retrieval, ID mapping, Swiss-Prot/TrEMBL. For Python workflows with multiple databases, prefer bioservices (unified interface to 40+ services). Use this for direct HTTP/REST work or UniProt-specific control.
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