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Found 619 Skills
Use this skill when a user asks to review a pull request for bugs, wants AI code review focused on correctness issues, or runs /bug-review. Trigger on PR review, bug finding, code review, "review this PR", "check for bugs", "find issues in this PR". This is a multi-pass review workflow with 5 parallel passes, majority voting, independent Opus validation, and resolution rate tracking. Also trigger on /bug-review:resolve to classify whether findings were fixed at merge time, and /bug-review:report for resolution rate stats. Even if the user just says "review this" while on a PR branch, trigger this skill.
Capture the current session's repeatable process into a reusable SKILL.md skill file. Use when the user wants to create a skill, save a workflow as a skill, turn a process into a reusable skill, or mentions "skillify", "create skill", "make a skill", "save as skill", "capture workflow", "turn this into a skill", "new skill", or wants to automate a repeatable process they just performed.
Build your app's primary user interface embedded in the Shopify admin. If the prompt just mentions `Polaris` and you can't tell based off of the context what API they meant, assume they meant this API.
Sets up or repairs the AGENTS.md source-of-truth pattern for any project. Creates a well-structured AGENTS.md with real stack info auto-detected from the project, then wires all AI config satellites (.claude/CLAUDE.md, .github/copilot-instructions.md, .agents/rules/, MEMORY.md) to point to it. Eliminates duplication. Always runs in plan mode — asks before acting. Use this skill whenever the user mentions AGENTS.md, agent config, source of truth for AI rules, setting up Claude/Copilot/Cursor for a project, fixing duplicate AI instructions, or wants to consolidate AI configuration files. Trigger even if the user just says "set up agents" or "fix my AI config".
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.
Phase 3 of the feature workflow – Complete the acceptance closed-loop. Four tasks: 1. Check layer by layer against {slug}-design.md to verify if the implementation deviates from the plan; fix any deviations on the spot instead of just "noting them" in the report. 2. Incorporate this feature into the project's overall architecture documentation. 3. If this feature changes the user story or boundaries of the corresponding requirement, update the requirement doc accordingly. 4. If this feature originated from a roadmap item, change the status of the corresponding entry in roadmap items.yaml to done and sync it with the main document. Finally, produce a {slug}-acceptance.md as the closed-loop proof for the entire workflow. Prerequisite: cs-feat-impl is completed. Trigger scenarios: User says "The feature is done, let's accept it", "Do the final check", "Prepare for merge", "Generate the acceptance report".
Behavior Guidelines for Information Visualization Presentation. Automatically activated when the model's response contains structured information such as comparisons, steps, configurations, architectures, etc., ensuring priority use of visual formats like tables, code blocks, lists, tree structures, instead of pure text accumulation. Trigger words: "Use a table", "Draw a diagram", "Make a list", "Structure it", "Don't just use text", "Visualize", "Compare". Even without trigger words, the rules of this Skill should take effect as long as the response contains structured information suitable for visualization. It also applies to scenarios such as "Too much text to read", "Can it be more intuitive?", "Organize into a table".
Startup diagnostic router. Use FIRST when a founder doesn't know where to start, has multiple overlapping problems, or asks a vague question like 'what's wrong with my startup', 'why aren't people buying', 'what should I focus on', 'where do I even begin', 'nothing is working'. Routes to the right framework from the 14 available skills — or tells you when no framework fits and you just need to go talk to people. This is the entry point. Use it before reaching for any specific skill.
Candlestick / OHLCV data and intraday minute series for stocks listed in HK / US / A-share / Singapore via Longbridge Securities. Supports 1m / 5m / 15m / 30m / 1h / day / week / month / year periods, history by date range, and today's intraday curve. Triggers: "K线", "K 线", "走势", "历史价格", "日K", "月K", "周K", "分时图", "近一周走势", "K線", "走勢", "歷史價格", "日K", "月K", "週K", "分時圖", "candlestick", "candles", "OHLCV", "intraday chart", "price history", "weekly chart", "monthly chart", "1-year chart", "前复权", "前復權", "forward adjusted".
Prioritize drug targets from a ranked gene list (e.g., scRNA-seq DE output) by orchestrating parallel API queries against UniProt, OpenTargets (with integrated DepMap CRISPR essentiality + gnomAD constraint), PubMed, the Human Protein Atlas (HPA), and ChEMBL tool compounds, then re-ranking by a composite score combining protein localization, druggability, disease genetics, tissue specificity (safety), focus-cell-type expression, CRISPR essentiality, LoF safety constraint, and research maturity. Use whenever the user wants to filter, triage, prioritize, or "do due diligence" on a list of candidate genes for drug discovery, especially after a DE / DEG analysis when they say things like "which of these should I follow up on", "filter for druggable targets", "make a target dossier", "rank these for tractability", "annotate these genes for druggability", or "build a target report". Trigger even when the user says just "filter these candidate genes" or hands over a CSV from a DE pipeline.
Verify Next.js runtime behavior after editing app code. Use this skill to confirm a change actually works in a running app — not just that it compiles or type-checks. Combines /_next/mcp (Next.js's view) with agent-browser (the browser's view). Requires a running `next dev`.
Analyze source code and produce an enterprise-quality, domain-organized Wiki under `.nium-wiki/`. Trigger on: "generate wiki", "create docs", "update wiki", "rebuild wiki", or any documentation generation request. Capabilities: - Semantic code analysis — understands logic, not just structure - Auto-generated Mermaid diagrams (architecture, data flow, class, dependency) - Bidirectional cross-linking across all documents - SHA256-based change detection for incremental rebuilds - Every section traces back to source via relative path links - Multi-language output (zh/en/ja/ko/fr/de and more)