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Found 36 Skills
Use when the user is starting a new project or feature, or mentions "concept", "roadmap", "feature", "spec", "plan", "idea", or "what to build". Walks them through three plain-English phases — Concept (what & why) → Roadmap (the path) → Features (the work) — producing one-page markdown artifacts under `specdriven/` that anchor every later turn. Skip when the task is already small and well-scoped (a rename, a one-line bug fix).
Vercel AI SDK expert guidance. Use when building AI-powered features — chat interfaces, text generation, structured output, tool calling, agents, MCP integration, streaming, embeddings, reranking, image generation, or working with any LLM provider.
Ultra-lightweight channel for feature workflows: No need to write design docs, checklists, or conduct phased reviews. Let AI write code directly as it normally would, but before it starts, tell it where the CodeStable knowledge base in the project is and how to search it. This way, the code it writes will have fewer pitfalls and be more consistent with project conventions. Trigger scenarios: Users say "fast mode", "fastforward", "skip all those steps", "just start coding", "help me make xxx" and the requirement is too small to go through the design process.
The drum sounds. Bloodhound, Elephant, Turtle, Beaver, Raccoon, Deer, Fox, and Owl gather for complete feature development. Use when building a full feature from exploration to documentation — secure by design.
Specialized feature development agents. Use for deep codebase exploration and architecture design during feature development.
Orchestrator skill for the complete feature development lifecycle. Coordinates 5 phases - task selection, component design, build loop, analytics setup, and commit/documentation. Use when building any new feature or enhancement that requires multiple steps.
Implementation guide for new Streamlit features. Use when adding new elements, widgets, or features that span backend, frontend, and protobufs.
Use when starting new feature work to create isolated git worktrees with smart directory selection and safety verification. Keeps main branch clean while developing.
Use when developing a new feature, fixing a bug, or making significant code changes - guides the full cycle from planning through verified commit with expert review
Transform code, issues, or context into a detailed prompt/context for another LLM to fix or implement. Use when preparing comprehensive context for external LLM assistance, bug fixes, improvements, or feature implementations. Provides detailed context without implementation suggestions, letting the receiving LLM decide how to implement solutions. Focuses on "what" (problem, requirements, current state) not "how" (implementation approach).
Fast Track for Feature Process - When requirements are clear and scope is small, skip the complete design process, write a compact {slug}-design.md, and proceed directly to implementation after one confirmation from the user. What is compressed is divergent discussions and phased reviews, not quality standards - code pointers, acceptance criteria, etc., must not be omitted. Trigger scenarios: User says "quick mode", "fastforward", "cut the steps", "just start working". Not suitable for complex features involving cross-subsystem integration, new terminology sorting, or more than 4 promotion steps - in these cases, proactively inform the user to revert to the complete process.
When developing new features, follow this sub-process — take the vague idea of "add X capability" through to the acceptance closure, with solution documents archived so that both AI and users can later check the original thinking and decision rationale. Trigger scenarios are focused on adding new capabilities ("develop new feature", "add X", "implement XX"), and do not handle bugs in existing code. This skill only acts as a router, deciding which sub-skill to trigger next among brainstorm / design / fastforward / implement / acceptance based on existing artifacts.