Results for “plain”

Work with Obsidian vaults (plain Markdown notes) and automate via obsidian-cli.

Work with Obsidian vaults (plain Markdown notes) and automate via obsidian-cli.

Writes documents in a plain, human voice and removes phrasing that reads as machine-generated, applying a two-pass write-and-audit process to any written artifact meant to be read by a person.

Transforms plain text or markdown into well-structured, reader-friendly markdown with frontmatter, titles, summaries, headings, bold, lists, and code blocks.

Formats plain text or markdown files into well-structured markdown with frontmatter, headings, bold, lists, and typography fixes, outputting a new formatted file.

Generates a single unified changelog from git history, written in plain language for the whole company, defaulting to Slovak and comparing the release branch against develop for unreleased changes.

Creates a self-contained interactive HTML explanation of code changes, including background, intuition, code walkthrough, and quiz sections, with diagrams and responsive styling.

Write user-facing copy following Sentry's brand guidelines, covering Plain Speech and Sentry Voice tones for UI text, documentation, and marketing content.

Guides contributors through adding, updating, publishing, documenting, validating, and wiring public skills in the BuilderIO/skills repository, covering plain skills, instruction-style skills, app-backed/MCP skills, and Plan skill sync.

Creates a clean horizontal-swipe HTML deck for pitches, overviews, or study materials with cover, content pages, progress bar, and keyboard navigation.

Technical writing proficiency covering clarity principles, audience analysis, information structure, editing techniques, and style enforcement. Use when writing or improving any technical content — docs, specs, guides, or explanations. Also trigger for 'technical writing', 'write clearly', 'simplify this', 'rewrite for clarity', 'plain language', 'writing style', or 'editing pass'.

Create, edit, and run plain-text MATLAB live scripts (.m files) with rich text formatting, LaTeX equations, section breaks, and inline figures. Use when generating tutorials, analysis notebooks, reports, documentation, or educational content, when modifying existing live scripts, or when converting existing binary .mlx files to .m for version control. Requires R2025a+.

Reads URLs and PDFs by fetching source content, defaulting to concise summaries for plain read requests and clean Markdown when asked to convert, save, quote, cite, or feed downstream work. Use when users ask in any language to read, fetch, check, summarize, quote, cite, convert, or save a URL or PDF. Not for local text files already in the repo.

Correct grammar errors, typos, and improve academic readability in LaTeX, Markdown, or plain-text manuscripts. Scans the document once, then walks through every issue one-by-one asking for approval before applying each fix. Trigger when the user says "readability", "check grammar", "fix typos", "proofread for grammar", "improve readability", "polish wording", "语言润色", "修语法", or asks you to clean up the prose in a paper/chapter/section without wanting full content restructuring.

Build the operator knowledge base future-you and any AI can actually search. Capture facts, playbooks, stakeholders, and how-tos as plain greppable markdown, organized so the answer is a search away instead of a memory or a Slack scroll. Trigger on "start a knowledge base", "write this down somewhere findable", "document how we do this", "who owns what again", "capture this for later", or any fact you have now looked up more than once.

Stop re-litigating decisions you already made. Keep a decision record where each entry captures the decision, the context that forced it, the options you weighed, why you chose, and when to revisit, one entry at a time, in plain searchable markdown you can grep later. Trigger on "log this decision", "why did we choose X", "write a decision record", "record why we're doing this", "what did we decide about", or any moment a real call gets made and would otherwise be forgotten.

Add captions or subtitles to an existing single-subject talking-head video without editing the footage. Use for plain verbatim captions, cinematic captions embedded behind the subject, VFX captions, “炸/特效/酷炫字幕,” or a named identity from the 35-style catalog. Route by visual identity, not by backend engine. The quiet `anchor` rail is the default; embed every word only when the user explicitly wants a fully cinematic treatment. The workflow runs locally end to end, including transcription and subject matting; split multi-shot footage before applying it.

Generate user-friendly "Explain Like I'm 5" feature documentation for end users by reading the codebase. Use this skill whenever the user wants to document a feature for non-technical users, write help docs, create an explainer for a feature in their app, produce onboarding content, or asks "make a user doc for X". Trigger on phrasings like "ELI5 the closeout flow", "write user docs for the kanban view", "explain this feature to a customer", "make a help article for X", "document this for end users". Also known as "E-features-LI5". This skill produces plain-language docs written for someone with the app open trying to get something done — not internal developer docs (use the `teach` skill for those) and not feature announcements.