Results for “natural-language”

Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's comprehensive "Signs of AI writing" guide. Detects and fixes patterns including: inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, negative parallelisms, and excessive conjunctive phrases.

Navigation aid for the processkit skill catalog — maps natural-language cues and task types to the right skill. Read this when you are unsure which skill applies to the current task, when the user names a task without naming a skill, or at session start when orienting to an unfamiliar project. Always the first skill to consult; never the last.

Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's comprehensive "Signs of AI writing" guide. Detects and fixes patterns including: inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, negative parallelisms, and excessive conjunctive phrases.

Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's comprehensive "Signs of AI writing" guide. Detects and fixes patterns including: inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, negative parallelisms, and excessive conjunctive phrases.

Create or update a MoonSpec feature specification from a natural language feature request or referenced declarative design. Use when the user asks to run or reproduce `/moonspec.specify`, create a `spec.md`, initialize a feature directory under `specs/`, preserve the original feature request for later verification, map source design requirements, or generate a single-story MoonSpec specification with a requirements quality checklist.

This skill should be used when the user asks to "understand a codebase", "get code context", "research a library", "explore a repository", "find code examples", "look up documentation", asks a natural-language code/technology question (e.g. "how does X work", "X vs Y", "best practice for Z"), or wants to understand how a specific project, library, or concept works before making changes.

Google Calendar integration for viewing, creating, and managing calendar events. Use when the user asks about their schedule, wants to add/edit/delete events, check availability, or needs a morning brief. Supports natural language like "What's on my calendar tomorrow?" or "Schedule lunch with Alex at noon Friday." Free tier provides read access; Pro tier ($12) adds create/edit/delete and morning briefs.

Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's comprehensive "Signs of AI writing" guide. Detects and fixes patterns including: inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, negative parallelisms, and excessive conjunctive phrases. Credits: Original skill by @blader - https://github.com/blader/humanizer

AI-powered crypto trading agent, wallet API, and LLM gateway via natural language. Use when the user wants to trade crypto, check portfolio balances (with PnL and NFTs), view token prices, search tokens, transfer crypto, manage NFTs, use leverage, bet on Polymarket, deploy tokens, set up automated trading, sign and submit raw transactions, or access LLM models through the Bankr LLM gateway funded by your Bankr wallet. Supports Base, Ethereum, Polygon, Solana, and Unichain.

Breaks natural-language problem descriptions into sub-tasks suitable for DAG nodes. The entry point of the meta-DAG. Identifies phases, dependencies, parallelization opportunities, and vague/pluripotent nodes that can't yet be specified. Uses domain meta-skills when available. Activate on "decompose task", "break down problem", "plan workflow", "what are the steps", "sub-tasks", "task breakdown". NOT for executing the decomposed tasks (use dag-runtime), building the DAG structure (use dag-planner), or matching skills to nodes (use dag-skills-matcher).

Fast, accurate code search for AI agents using ~98% fewer tokens than grep+read. Indexes any local or remote repository in under a second (~250ms on CPU, no GPU or API key needed). Supports natural-language and symbol queries, semantic similar-code discovery, and MCP server integration for Claude Code, Codex, Cursor, and OpenCode. Python library available for programmatic use. Triggers on: semble, code search, semantic code search, semble search, token-efficient search, find code, code search mcp, agent code search, semble find-related, semble savings.

Generate and conversationally edit short videos with Google Gemini Omni Flash (`gemini-omni-flash-preview`). Use when: (1) iterating on a clip with natural-language edits instead of regenerating ("make the phone invisible, keep everything else the same"), (2) generating 3-10s 720p clips with synthesized audio, rendered on-screen text, or timecoded beats, (3) binding reference images to roles with <FIRST_FRAME>/<IMAGE_REF_N> prompt tags, (4) editing an existing uploaded video. Accessed via the `gemini_omni_video` tool using the project's GEMINI_API_KEY/GOOGLE_API_KEY — the same key as Imagen and Google TTS.

Produce a plain-language manual test plan from the context supplied to it — an executive summary, a high-level list of named tests, and a detail section per test with the steps a person follows by hand and the outcomes they should expect. Use when you want to create, draft, generate, or outline a manual test plan, manual QA steps, hands-on verification steps, or an acceptance walkthrough for a feature, change, branch, plan, or PR. When the plan holds more than five tests and at least two natural categories emerge, both the test list and the detail sections are organized under plain-language categories. When nothing in the supplied context can be manually tested, it says so and asks for more context instead of producing a document. Does not analyze code for automated test coverage gaps — use automated-test-planning. Does not write test code — use tdd. Does not review code quality — use code-review. Does not stress-test an existing plan — use iterative-plan-review.

The craft of designing icons that communicate instantly across cultures, contexts, and scales. Icon design bridges semiotics, cognitive psychology, and visual craft to create symbols that users understand without thinking. Great icons are invisible in the best way - they convey meaning so naturally that users never pause to decode them. This skill covers icon grid systems, optical alignment, stroke consistency, metaphor selection, scalability across sizes, SVG optimization, and icon set coherence. The best icon designers understand that icons are a visual language - each icon must speak the same dialect while carrying its own distinct meaning. Use when "icon, iconography, symbol, glyph, icon set, icon library, pictogram, svg icon, icon grid, icon pack, feather icons, lucide, phosphor, heroicons, icon system, icon style, icons, iconography, svg, symbols, glyphs, pictograms, ui-icons, icon-set, visual-design, design-system" mentioned.

Turn natural-language descriptions into editable `.drawio` diagrams and export them to PNG / SVG / PDF / JPG via the native draw.io desktop CLI, or turn an existing codebase (Python / JS-TS / Go / Rust) into an auto-laid-out structure diagram. Wraps Agents365-ai/drawio-skill: 6 diagram presets (ERD, UML class, sequence, architecture, ML/DL, flowchart), search across 10,000+ official AWS/Azure/GCP/Cisco/K8s/UML/ BPMN shapes, 321 AI/LLM brand logos, vision self-check + auto-fix, and a 5-round iterative refinement loop. No MCP server, no daemon — runs from a single SKILL.md and the draw.io CLI. Use when the user wants polished, precise, exportable diagrams or wants to visualize code structure. Triggers on: drawio, draw.io, drawio diagram, architecture diagram, ERD, UML diagram, sequence diagram, flowchart, network diagram, visualize codebase, code structure diagram, class hierarchy, export diagram png/svg/pdf, AWS/Azure/GCP icon, draw.io shapes.

Generate browser walkthrough recordings as GIF and MP4 from a natural language description. Use this skill whenever the user wants to record a browser walkthrough, create a product demo, document a UI flow, generate onboarding visuals, or produce a "how to" screen recording for any web app. Triggers include: "record a walkthrough of", "create a GIF showing how to", "make a demo of", "capture the flow for", "show how [feature] works in the browser", "document this UI flow", or any request combining a browser/web app with recording/capture/demo output. The skill generates a local Node.js/TypeScript project that the user runs on their machine using Stagehand + Playwright for AI-controlled browser automation, and gifski/ffmpeg for output. For quick one-off captures in the user's live browser session, prefer the claude-in-chrome gif_creator tool instead; use this skill when a re-runnable script, MP4, high-quality GIF, clean-profile recording, or CI repeatability is needed.