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Found 549 Skills
Novel content polishing and optimization, suitable for user requests such as "Help me polish this novel", "Improve the writing style", "Optimize chapter rhythm", "Enhance this highlight", "Make dialogues more natural", "Make this passage more engaging", "Optimize novel writing style", "Adjust chapter rhythm", "Make dialogues more realistic", "Help me revise this content", "Polish novel", "Optimize highlights", "Improve writing style", "Make this passage more immersive", etc. It provides 3 levels of polishing, focusing on optimization of writing style and content, supporting special optimizations such as style adaptation, rhythm tightening, highlight enhancement, dialogue optimization, etc. **Polished results directly modify the chapters/ directory, and automatic backups are made to .sumeru/write/original/ before modification**. **Sub-Agents are used for parallel processing during batch polishing, with each Agent responsible for a maximum of 3 chapters**
MUST be used whenever fixing security issues in a Flows app, or before shipping any feature that handles credentials, user input, or external data. This skill finds AND fixes security problems — it does not just report them. Do NOT skip this when the user asks for a security fix, security hardening, or vulnerability remediation — run every step in order. Triggers: security, security fix, security hardening, vulnerability, XSS, injection, credentials, secrets, auth, authentication, authorization, token, sensitive data, input validation, CORS, CSP, dependency audit.
Amend a published CLI from one of two input sources: (1) dogfood mode mines the active Claude Code session transcript for friction (missing flags, hand- rolled API payloads, silent-null returns); (2) direct-input mode accepts user-supplied asks (rename a command, add commands or feeds, fix a named bug, optionally sniff the source site for new endpoints). Confirms scope with the user, plans + executes the fix autonomously, scrubs PII, and opens a PR against mvanhorn/printing-press-library. Two user-in-loop checkpoints: scope after capture, PR draft before open. Trigger phrases: "amend the CLI", "submit a patch", "fix what I just dogfooded", "open a PR for this CLI", "patch this CLI", "add features to my CLI", "rename this command", "add these feeds to <cli>", "sniff for new APIs in <cli>", "amend with these ideas", "use printing-press-amend", "run printing-press-amend".
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)
Use when complex problems require systematic step-by-step reasoning with ability to revise thoughts, branch into alternative approaches, or dynamically adjust scope. Ideal for multi-stage analysis, design planning, problem decomposition, or tasks with initially unclear scope.
Master deep work productivity through the three types of work framework (Building, Maintenance, Recovery). Use when user needs to: (1) Build a sustainable deep work routine with just 1 hour/day, (2) Create vision/anti-vision for life direction, (3) Structure goals using the 10-year → 1-year → 1-month → 1-week hierarchy, (4) Apply project-based learning to bridge skill gaps, (5) Identify lever-moving tasks that actually progress goals, (6) Balance focus work with necessary recovery for creativity.
The meta-skill that powers all other AI tools. Prompt engineering for creative applications is the art and science of communicating with AI models to produce exactly what you envision—in images, video, audio, and text. This isn't just "write better prompts." It's understanding how different models interpret language, how to structure requests for different modalities, how to iterate systematically, and how to build prompt libraries that encode your creative vision. The best prompt engineers have developed intuition for what words trigger what responses in each model. This skill is foundational—it amplifies the effectiveness of every other AI creative skill. Master this, and you master the interface to all AI creation. Use when "prompt, prompting, prompt engineering, better prompts, prompt optimization, how to prompt, prompt strategy, prompt library, prompt template, make AI understand, prompt-engineering, prompting, meta-skill, ai-creative, foundational, optimization, iteration" mentioned.
Extract specific revenue guidance and growth projections from earnings call transcripts, including segment breakdown, constant currency adjustments, and M&A contributions.
Image Generation Skill: Use this skill when users need to generate images, create graphics, or edit/modify/adjust existing images. It supports 10 aspect ratios (1:1, 16:9, 9:16, etc.) and 3 resolutions (1K, 2K, 4K), and supports text-to-image and image-to-image editing.
Transform an AI agent into a tasteful, disciplined development partner. Not just a code generator, but a collaborator with professional standards, transparent decision-making, and craftsmanship. Use for any development task: building features, fixing bugs, designing systems, refactoring. The human provides vision and decisions. The agent provides execution with taste and discipline.
Guides creation of effective Agent Skills with proper structure and validation. Use when users want to create a new skill, update an existing skill, or need guidance on skill design patterns, SKILL.md format, or verify.py implementation. NOT when just using existing skills (use those skills directly).
Systematic methodology for debugging bugs, test failures, and unexpected behavior. Use when encountering any technical issue before proposing fixes. Covers root cause investigation, pattern analysis, hypothesis testing, and fix implementation. Use ESPECIALLY when under time pressure, "just one quick fix" seems obvious, or you've already tried multiple fixes. NOT for exploratory code reading.