My agent skills for spec driven development and more
codevoyant is a collection of skills (slash commands) that give AI coding agents structured workflows for planning, development, and tooling. Works with Claude Code, OpenCode, and VS Code Copilot.
Workflows
| spec — plan and execute complex work Research requirements, generate proposals, create phase-by-phase implementation plans, and execute them step-by-step or hand off to a background agent. | |
| dev — architecture and exploration Architecture planning, technical exploration, and repo/branch comparison. | |
| docs — engineering documentation Generate, update, review, and retroactively create docs from standard templates. | |
| flow — end-to-end pipeline orchestration Chain skill workflows into end-to-end pipelines that run sequentially. | |
| pr — AI-powered code review Generate professional inline review comments from a diff, address change requests, and publish a draft review. | |
| qa — bug investigation and smoke testing Structured bug investigation, browser-agent smoke tests, one-command issue filing to GitHub, GitLab, or Linear. | |
| skill — build, maintain, and report skills Scaffold new skills, iterate on existing ones, audit quality, and report issues to skill authors. |
Domains (experimental context skills for specialized engineering)
| em Experimental — engineering project planning Milestone-grouped task plans, capacity and dependency review, and sync with Linear. | |
| pm Experimental — product roadmaps and PRDs Phased roadmaps, per-feature PRDs, prioritization review, and Linear initiative sync. | |
| ux Experimental — prototyping and style research Scaffold SvelteKit prototypes, create single-file wireframe explorations, and extract styles from live sites. | |
| compgeo Experimental — computational geometry 3D formats, bounding boxes, voxels, point clouds, feature extraction (CGAL), ray tracing, GLTF, SDFs, rotations/quaternions, OpenVDB ops — Python, C++, TypeScript. | |
| hpc Experimental — high-performance computing C++ threading, OpenMP, TBB, SIMD, CUDA, SYCL, MPI, Python parallelism, Ray, Thrust, Kokkos, and NVIDIA Warp GPU kernels. | |
| mle Experimental — ML engineering Data pipelines (Ray Data), distributed training, model eval, TensorBoard, MLflow, model publishing, data curation, Label Studio, DVC versioning, data loaders. | |
| llm Experimental — LLM engineering AI SDK and LangGraph agents, tool calling, document/image processing, open-weight model serving on AWS/GCP, RAG (AWS/GCP/OSS), and LLM eval tooling. |
Tools
| changelog — retcon PR/MR commit messages and preview the next changelog | |
| cz — show current and predicted next version using commitizen | |
| docker — multi-stage builds, Compose, cross-platform networking, GCP registry | |
| gcp — Artifact Registry, Cloud Run deploy, gcloud auth, service account patterns | |
| gh — Watch Actions pipelines, fetch and post inline PR review comments, manage draft reviews | |
| git — conventional commits with auto-formatting and safe interactive rebase | |
| glab — watch CI pipelines, fetch and post inline MR discussion notes, manage draft reviews | |
| helix — Helix editor key bindings for file navigation and selection-based workflows | |
| linear — create Linear issues and bug reports via MCP Linear tools | |
| mise — mise.toml authoring, task naming conventions, language-specific setup recipes | |
| release — show current and predicted next version via semantic-release or release-it | |
| task — detect and run tasks across mise, just, task.dev, and npm scripts | |
| terraform — directory structure, backend config, workspace-per-environment for GCP and AWS | |
| vim — Vim and Neovim key bindings for file navigation, search, and splits |
Frameworks
| react — Zustand state management, shadcn/ui and Tailwind, React Three Fiber and Drei, data fetching | |
| sveltekit — feature-slice architecture, Svelte 5 runes, shadcn-svelte, a11y, form patterns | |
| tanstack — TanStack Start file-based routing, Router v1, Query v5, Form, server functions |
Languages
| cpp — CMake project structure, Conan package management and publishing, gRPC service patterns, code standards, release profiles | |
| python — uv workspace and publishing, MLflow tracking, Ray distributed training, Warp GPU kernels, Pydantic, Click CLIs | |
| typescript — pnpm workspaces, publishing, Vitest, ESLint flat config, GitLab CI |
npx skills add cloudvoyant/codevoyant
curl -fsSL https://raw.githubusercontent.com/cloudvoyant/codevoyant/main/scripts/install-opencode.sh | bash
curl -fsSL https://raw.githubusercontent.com/cloudvoyant/codevoyant/main/scripts/install-vscode.sh | bash
# Plan and execute a feature /spec new my-feature # explore requirements and create a plan /spec go my-feature # execute step-by-step with review stops /spec bg my-feature # hand off to a background agent # Ship code /git commit # format → conventional commit → push /gh ci --autofix # watch GitHub Actions, auto-fix failures and re-push /glab ci --autofix # watch GitLab CI, auto-fix failures and re-push # Review a PR/MR /pr new # generate inline review comments from the diff /pr address # pull reviewer feedback and propose fixes # Plan engineering work /em plan "migrate auth to OAuth2" # milestone-grouped task plan /em review my-plan # capacity and risk review # Plan product work /pm plan quarter # draft quarterly roadmap /pm prd "user authentication" # standalone PRD # Build a skill /skill new my-command # scaffold from template /skill critique my-command # audit quality before shipping /skill feedback spec # report an issue to skill authors
See the full documentation →
MIT © Cloudvoyant