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Found 2,007 Skills
Use when you need to generate "page list → function points → business processes → business rules" with evidence from frontend code, and the project has non-unique routing entries, complex dynamic routes/permissions/backend menus, and the team is prone to making assumptions or missing evidence chains.
Board meeting preparation, investor updates, and executive communication. Use when preparing board decks, writing investor updates, handling bad news with the board, structuring QBRs, or building board-level metric discipline. Includes the "Three Things" narrative model, the 4-tier metric hierarchy, and the pre-brief pattern that prevents board surprises.
Use when you need to generate `{FEATURE_DIR}/verification/report-{date}-{version}.md` (test report) during the verification phase of Spec Pack, provide deliverable conclusions that are traceable to test cases and defect references.
Use when you need to execute R3 (Prototype Generation) in the product requirement Spec process of sdlc-dev, generate requirements/prototype.md based on requirements/prd.md (including task flow + page structure + ASCII wireframe + AC mapping + walkthrough script), and avoid proceeding with generation without context/PRD, using Open Questions instead of verification checklists, or using non-ASCII formats that make the prototype untraceable and unreviewable.
Visual whiteboard collaboration for Copilot CLI. Creates an interactive whiteboard that opens in your browser — draw, sketch, add sticky notes, then share everything back with Copilot. Copilot sees your drawings and text, and responds with analysis, suggestions, and ideas.
Use this when you need to execute R4 (generate an interactive Demo project based on requirements/prototype.md) in the sdlc-dev product requirement Spec process, and need to avoid skipping spec-context, proceeding when prototype.md is missing or the runnable Demo project root directory is missing, or creating custom pages/directories that lead to untraceability and inability to close the loop.
Perform a systematic diagnostic scan of an AI workflow across 5 quality dimensions — prompt quality, context efficiency, tool health, architecture fitness, and safety — producing a scored report with prioritized remediation actions.
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
This skill should be used when the user asks about service status, wants to rename a service, change service icons, link services, or create services with Docker images. For creating services with local code, prefer the `new` skill. For GitHub repo sources, use `new` skill to create empty service then `environment` skill to configure source.
Use when the user wants to build or tailor a resume, detailed interview resume, career master run, career coach, interview coach, career knowledge vault, Obsidian/LLM wiki, professional DOCX template, visual HTML/PDF resume, Canva-ready or Figma-ready resume, ATS/recruiter scorecard, cover letter, LinkedIn recommendations, interview prep, project interview briefs, technical-stack guide, job match scoring, redaction review, or career evidence summary from LinkedIn content, local project docs, Confluence, Jira, public GitHub, GitHub Enterprise, open-source work, profile pictures, or job postings. Trigger for resume drafting, tailoring, full career timeline, roles and responsibilities, impact metrics, ATS checks, keyword matching, DOCX generation, visual design tools, Canva/Figma handoff, browser/PDF rendering, project evidence extraction, recursive workspace analysis, durable career memory, tool auditing, job search, and interview prep.
Review a pull request diff and write structured feedback to review.json for the workflow to publish. Use when reviewing a checked-out PR from local artifacts like pr_diff.txt and pr_description.txt and producing machine-readable review output instead of posting directly to GitHub.
Produce a polished, self-contained HTML "readout" document under ~/.readouts (with an auto-maintained index page), either by snapshotting the findings accumulated in the current conversation or — when invoked fresh, e.g. "/readout on how github webhook events are processed" — by sharpening scope with clarifying questions and researching the codebase before documenting. The work runs in a child agent so the main conversation's context stays clean. Use whenever the user invokes /readout, says "write this up", "turn this into a doc/page", "make a readout", or asks for a readable, shareable document capturing findings or explaining how something works.