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Requires OFOX_API_KEY — create one at https://app.ofox.ai. Change one thing in an image you already have and leave the rest of the picture alone — swap the background, recolour a part, remove or add an object, clean up a photo — from a local jpeg/png/webp file. Delegates to ofox-image-core's `edit` subcommand (POST /v1/images/edits, one synchronous request), prices the job with --dry-run before spending, and reports the real token cost including the uploaded picture, which is billed. Use when a user hands over an image and asks for a change to it, e.g. "change the background of this photo to a beach and keep the person unchanged", "make this button green", "remove the car in the background", or "put this product on a plain white background". Do not use to draw a new image from a text description with no input picture (that is ofox-image-core's `generate`), to produce a set of several images to choose between (see product-image), or to turn a photo into video (see seedance-product-video or seedance-ad-creative). Editing the content of an existing video — "change the background of my clip, keep the product" — has no route here and none in the video API either (measured; the mode field an edit would use is accepted and silently ignored, so nothing errors); this skill edits a single still, and routing such a request to a video skill generates brand-new footage instead of changing theirs.

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Requires OFOX_API_KEY — create one at https://app.ofox.ai, plus the music file the finished video must carry. Your audio never reaches the API (measured) — the visuals are written to the track's tempo, mood and sections, then your own file is laid on locally at zero cost. One job caps at 30 seconds, so a three-minute song is six jobs minimum and the cost table says that before anything is spent. Use when a user has a specific piece of music and wants visuals for it, e.g. "make a music video for this track", "visuals for my song", "an MV for this instrumental", "generate footage cut to this beat". Do not use for cheap vertical social drafts (shorts-reels), a brand film that happens to have a music bed (seedance-ad-creative), or when there is no particular audio file the finished video has to carry.

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Turns client wins into structured case studies in multiple formats. Gathers before/after metrics, structures as Problem-Solution-Results, and outputs landing page copy, one-pager, social snippets, and email insert.

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Generate full prospect audit as a sales tool before demos. Combines company research, CRO audit, and person intel into a presentable document with talking points and opportunity sizing.

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On-page SEO optimization for existing content with before/after scoring

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Convert Claude's Markdown output to each channel's native text syntax before delivery. Adds zero-dependency formatting for WhatsApp, Telegram, and Slack (marker substitution). Also ships a Signal rich-text helper (parseSignalStyles) used by the Signal skill.

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在用户已经完成一次 implementation 工作后，把项目里的 implementation plan + git diff/log 渲染成一份单文件 HTML 实施报告。报告包含 TL;DR、风险概览、架构图（mermaid）、Before/After 数据流、决策记录卡片、风险清单。用于开会前快速对齐团队、向 reviewer 解释设计决策、归档实施叙事。当用户说"生成实施报告"、"impl-explain"、"explain implementation"、"展示这次实施方案"、"做一份 HTML 实施总结"时调用本 skill。

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Use at the start of every session and before completing any coding task.

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Use before declaring any coding task complete, done, or finished.

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Use before starting any coding task when Superpowers is not present.

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Guides an agent through reproducing, root-causing, fixing, and validating flaky tests in the PostHog monorepo. Use when a test fails intermittently in CI but passes on rerun or locally, when `hogli ci:insights` or the debugging-ci-failures skill classifies a failure as a flaky test, when given a GitHub Actions URL for a flaky job, when asked to check Trunk Flaky Tests for a test, PR, or master, or when asked to deflake, stabilize, or fix a flaky Jest, pytest, or Playwright test. Core discipline: reproduce locally before changing anything, fix the root cause (never mask it with sleeps, retries, or bigger timeouts), and prove the fix with an N-run validation loop sized to the observed failure rate. Stabilizing is not the only valid outcome — the skill also gates whether the test should exist, so deleting a test that catches nothing real, or re-leveling one that flakes because of the level it runs at, are first-class endings.

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Use when the user requests React Doctor or a React code-health audit, or when a concrete React diagnostic question would benefit from its scan. Not a default step after React changes or before committing.

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