> **Quick Ref:** Execute single issue end-to-end. Output: code changes + commit + closed issue.

> **Quick Ref:** Decompose goal into trackable issues with waves. Output: `.agents/plans/*.md` + bd issues.

> **One job:** Tell a new user what AgentOps does and what to do first. Fast.

'Deep codebase exploration. Triggers: research, explore, investigate, understand, deep dive, current state.'

> **Purpose:** Run repeatable security checks across code, scripts, hooks, and release gates.

Spawn isolated agents to execute tasks in parallel. Fresh context per agent (Ralph Wiggum pattern).

> **Quick Ref:** Trace design decisions through CASS sessions, handoffs, git, and artifacts. Output: `.agents/research/YYYY-MM-DD-trace-*.md`

> **Purpose:** Is this code ready to ship?

Draft Diversity, Equity, and Inclusion statements for academic applications.

> **Source**: [https://github.com/aipoch/medical-research-skills](https://github.com/aipoch/medical-research-skills)

Access ENCORI (StarBase) database for miRNA-target, RNA-RNA, and other regulatory data. Invoke when user asks to search ENCORI or retrieve regulatory interactions.

Search FDA industry guidelines by therapeutic area or topic.

A Pythonic wrapper around RDKit with simplified interfaces and sensible defaults. Preferred for standard drug discovery workflows including SMILES parsing, standardization, descriptors, fingerprints, clustering, 3D conformer generation, and parallel processing. Returns native rdkit.Chem.Mol objects. For advanced control or custom parameters, use rdkit directly.

> **Source**: [https://github.com/aipoch/medical-research-skills](https://github.com/aipoch/medical-research-skills)

'Use when the user asks how to build with OpenAI products or APIs and needs up-to-date official documentation with citations (for example: Codex, Responses API, Chat Completions, Apps SDK, Agents SDK, Realtime, model capabilities or limits); prioritize OpenAI docs MCP tools and restrict any fallback browsing to official OpenAI domains.'

'Investigate bugs or audit code with repro evidence, root cause analysis, and fixes.'

'Audit, update, and validate dependencies, vulnerabilities, and licenses.'

'Validate product fit before discovery using PRODUCT.md and scope checks.'

'Create compact session handoffs for continuation after pause or compaction.'

'Repair skill hygiene: frontmatter, links, references, manifests, and parity drift.'

'Build an external-knowledge wiki from clipped articles, papers, and transcripts.'

'Use official OpenAI docs for API/product questions needing current citations.'

'Decompose goals into issue-ready plans, waves, dependencies, and validation checks.'

'Detect AgentOps setup and give one concise next action.'

'Explore a codebase or question and write evidence-backed findings.'

'Run repository security scans and release-gating checks.'

'Shared reference contracts used by other AgentOps skills.'

'Trace decisions and concepts through history, artifacts, and git.'

'Run full lifecycle: discovery, crank implementation, validation, and report.'

Use the `wtx` PowerShell CLI to create, navigate, and manage git worktrees for parallel development in this monorepo.

This provides essential guidance for AI coding agents working on this repository.

Research a codebase and create architectural documentation describing how features or systems work. Use when the user asks to: (1) Document how a feature works, (2) Create an architecture overview, (3) Explain code structure for onboarding or knowledge transfer, (4) Research and describe a system's design. Produces markdown documents with Mermaid diagrams and stable code references suitable for humans and AI agents.

Guidance for managing R package lifecycle according to tidyverse principles using the lifecycle package. Use when: (1) Setting up lifecycle infrastructure in a package, (2) Deprecating functions or arguments, (3) Renaming functions or arguments, (4) Superseding functions, (5) Marking functions as experimental, (6) Understanding lifecycle stages (stable, experimental, deprecated, superseded), or (7) Writing deprecation helpers for complex scenarios.

Build command-line apps in R using the Rapp package. Use when creating a CLI tool in R, adding argument parsing to an R script, turning an R script into a command-line app, shipping CLIs in an R package, or using Rapp (the alternative Rscript front-end). Also use for shebang scripts, exec/ directory in R packages, or subcommand-based R tools.

Create, manage, or connect to a headless Windows 11 VM running in Docker with SSH access. Use when the user wants to spin up, stop, restart, or SSH into a Windows VM.

This document describes the process of building a new skill in skills-for-fabric.

>

LDLS UI React design system rules (@ledgerhq/lumen-ui-react)

Build AI chat interfaces using ai-elements components — conversations, messages, tool displays, prompt inputs, and more. Use when the user wants to build a chatbot, AI assistant UI, or any AI-powered chat interface.

Creates a new Angular app using the Angular CLI. This skill should be used whenever a user wants to create a new Angular application and contains important guidelines for how to effectively create a modern Angular application.

Interactive briefing of a plan file — explains reasoning, schema decisions, component choices. Use when developers need to understand a plan before approving.

For standard implementation patterns, always check official guides first:

Enforce Elixir/Phoenix security — auth, OAuth, sessions, CSRF, XSS, SQL injection, input validation, secrets. Use when editing auth files, login flows, RBAC, or API keys.

Systematically maps mechanism evidence for a disease from molecules to pathways, cell types, tissues, biological consequences, and clinical phenotypes. Always use this skill when a user needs a layered mechanism evidence chain rather than a flat summary or immediate gap analysis. Formal literature citations must be real and verifiable.

Assesses whether a medical research topic is worth starting now by separating true novelty from pseudo-novelty, auditing real feasibility under stated resource constraints, and forcing a concrete start / narrow / redesign / stop decision. Always require explicit assumptions and never fabricate references, datasets, resource availability, precedent studies, or publication claims.

Precision editing tool that reduces abstract word count through intelligent compression techniques, maintaining scientific rigor while meeting strict journal and conference requirements.

1. Confirm the user objective, required inputs, and non-negotiable constraints before doing detailed work. 2. Validate that the request matches the documented scope and stop early if the task would require unsupported as.

1. Confirm the user objective, required inputs, and non-negotiable constraints before doing detailed work. 2. Validate that the request matches the documented scope and stop early if the task would require unsupported as.

1. Confirm the user objective, required inputs, and non-negotiable constraints before doing detailed work. 2. Validate that the request matches the documented scope and stop early if the task would require unsupported as.

Converts LabArchives notebook data, entry metadata, and authorized ELN exports into manuscript-ready academic writing outputs such as Methods sections, data-availability statements, reproducibility appendices, experiment timelines, and submission support notes. Optional bundled scripts can be used to collect or validate source notebook data before writing.