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Found 11,612 Skills
Reset the FPF reasoning cycle to start fresh
PRD/Requirement Document Anti-Omission Assistant. When a user provides a requirement document (PRD, functional specification, product document, etc.) and requests to generate front-end pages, implement functions, or carry out development, this Skill must be used first to convert the requirement document into a structured Checklist, then implement code module by module to prevent function omissions. Trigger scenarios: The user sends a .md/.docx/.pdf requirement document and asks you to "generate pages", "implement functions", "write code", "develop this system"; the user says "develop according to this PRD", "generate based on the requirement document", "implement this document"; the user provides a requirement description of more than 200 lines. Even if the user does not mention the checklist, this process should be automatically triggered if the input is a long requirement document (>200 lines) and the goal is to generate code.
Audit design documents for missing decisions, compatibility risks, rollout gaps, and observability omissions. Use whenever the user asks to review a design doc, architecture proposal, implementation-facing design, plan, or design-adjacent markdown file for completeness, migration strategy, rollback, data handling, or suggested additions without directly editing the document. Also trigger on short requests such as `review <file>.md` or `audit <file>.md` when the target looks like a design, plan, architecture, proposal, or decision document.
Ann — Master Orchestrator for MEL/SRHR work. Use when Ane brings any analytical, evaluation, SRHR, or structured-output task. Ann classifies task complexity, queries the MEL Wiki, retrieves knowledge, creates an implementation plan (verifies with user for complex tasks), delegates to Vi for execution, runs a 5-point quality gate, and delivers. General-purpose — not tied to any specific project.
RD Station integration. Manage Recordses. Use when the user wants to interact with RD Station data.
Shape conversation context (or a fresh task description) into a 5-part brief — Context / Task / Constraints / Verification / Output format — ready to hand off to an agent. Use when the user is ready to execute a task and wants it structured first. Composes naturally with /grill-me upstream, but works standalone too. Triggers: "/create-brief", "draft a brief", "shape this into a brief", "turn this into a task spec", "write a brief for this".
Initialize the .specify/ directory structure for Spec-Driven Development in the current project
LeadConnector integration. Manage Contacts, Companies, Opportunities, Users, Locations, Conversations and more. Use when the user wants to interact with LeadConnector data.
Meeting notes page — title bar with attendees, agenda checklist, decisions block, action items table with owners + dates, and a "next meeting" footer. Use when the brief mentions "meeting notes", "minutes", "1:1 notes", "all-hands recap", or "会议纪要".
Resize photos and videos to exact pixel dimensions or aspect ratios using Adobe tools. Use this skill whenever a user wants to resize, scale, or change the dimensions of an image or video file — including phrases like "resize this to 1920x1080", "make this 4K", "scale to 800x600", "change the aspect ratio to 16:9", "resize my video", "make the image smaller", "crop to square", "fit this to a specific size", "resize for print", "resize for web", "make it 300 DPI ready", "change canvas size", "resize a batch of photos", or any request specifying target dimensions (W×H, ratio, or named size like "4K", "HD", "A4"). Also triggers for: "make this fit a specific size", "resize to [any dimension]", "I need this at [WxH]", "scale my video down", "change resolution", "downscale", "upscale". NOT for social media platform sets (use adobe-create-social-variations for that). Uses image_crop_and_resize for photos, video_resize for videos.
Enerflo integration. Manage Organizations. Use when the user wants to interact with Enerflo data.
Set up an LLM-judge evaluation that extracts canonical use cases for a PostHog feature at scale and streams the results to a Slack channel as a live feed. Use when someone wants to understand how users are actually using a specific AI/LLM-powered feature in production — what they're investigating, what questions they're trying to answer, and what patterns surface — without manually reading hundreds of traces. Assumes the feature emits `$ai_generation` and `$ai_evaluation` events with `$session_id` linkage to the trigger user's recording (the standard setup post the session-summary linkage PRs).