Use when the user wants to read or search Microsoft Teams or Slack on macOS or Windows, including channels and DMs. Powered by LMCP, reading the desktop apps' local data.
日本語の概要は準備中です。原文の説明を表示しています。
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概要と使いどころ
Use when the user wants to read or search Microsoft Teams or Slack on macOS or Windows, including channels and DMs. Powered by LMCP, reading the desktop apps' local data.
日本語の概要は準備中です。原文の説明を表示しています。
Use when the user asks "what's on my plate today", "catch me up", "morning brief", or wants a summary of their day across calendar, reminders and email. The single most common multi-step automation. Powered by LMCP on macOS and Windows.
日本語の概要は準備中です。原文の説明を表示しています。
Use AtomLane to compile and execute safe atomic parallel plans on macOS and native Windows Preview for worthwhile independent argv tasks, dependency DAGs, supported platform entrypoints, or Apple-silicon operators. Use at task start or an execution boundary when structured local work may contain two or more worthwhile units; skip plain answers, one quick command, and work whose effects cannot be safely bounded.
日本語の概要は準備中です。原文の説明を表示しています。
Context engineering: compaction, progressive disclosure, structured notes via AgentDB. Triggers: tokens, compaction, memory, handoff, summarize, context window.
日本語の概要は準備中です。原文の説明を表示しています。
Use for UI/UX design, product flows, frontend or native interface design, design audits, design translation, asset planning, motion direction, design tokens, or distinctive non-generic apps and websites. Covers web and React, Windows and WinUI/Mica, Apple and SwiftUI, Android and Jetpack Compose/Material, cross-platform UI, and token export. Route to the focused skill, then load only the references required for the selected surface and failure mode.
日本語の概要は準備中です。原文の説明を表示しています。
Operate BurpSuite MCP Bridge for professional, authorized web testing. Use when Codex needs to inspect Burp live/history/logger/selection traffic, prioritize one target, retrieve a decisive request/response, intercept and edit a request or response before forwarding, replay one controlled mutation, manage temporary rewrite rules, import BChecks/Bambdas, export evidence, or diagnose the Windows Burp to WSL MCP connection.
日本語の概要は準備中です。原文の説明を表示しています。
Compose screen and interaction traps: navigation, adaptive layout, window insets, pagers, toolbars, sheets, list drag and selection, sliders, text fields, settings UI, one-shot effects. Use when layout, gestures or navigation misbehave.
日本語の概要は準備中です。原文の説明を表示しています。
Use the Crabbox wrapper for OpenClaw remote validation across Linux, macOS, Windows, and WSL2, including delegated Blacksmith Testbox proof. Report the actual provider and id.
日本語の概要は準備中です。原文の説明を表示しています。
Use when responding to an American Economic Review: Insights (AER: Insights) conditional-accept decision — addressing the editor's letter within the short window, usually without a second referee round. Drafts a concise, decisive response and revision plan; it does not redo the analysis (see aeri-robustness / aeri-identification).
日本語の概要は準備中です。原文の説明を表示しています。
Use when explaining or planning around ACM CCS peer review, the two-cycle HotCRP workflow, decision categories including minor revision, the rebuttal window, the adversarial reviewer pool, ethics and disclosure scrutiny, meta-review dynamics, and ACM proceedings outcomes.
日本語の概要は準備中です。原文の説明を表示しています。
Use when planning an ACL project calendar across ACL Rolling Review cycles, covering cycle selection against conference commitment windows, backward planning from an ARR deadline, the review-response-meta-review timeline, commitment decisions, resubmission loops to later cycles, and camera-ready through ACL Anthology publication.
日本語の概要は準備中です。原文の説明を表示しています。
Use when drafting an ACM CCS rebuttal during the HotCRP author-response window, covering threat-model defenses, adaptive-attack objections, ethics and disclosure questions, anonymity constraints, adversarial reviewer pushback patterns, and decision-focused replies aimed at the meta-reviewer.
日本語の概要は準備中です。原文の説明を表示しています。
Use when drafting an ACL author response inside an ACL Rolling Review cycle on OpenReview, covering the response window before meta-review, reviewer discussion dynamics, score-change strategy, flagging review issues to the area chair, anonymity rules, and deciding between responding now versus revising for a later ARR cycle.
日本語の概要は準備中です。原文の説明を表示しています。
Use when drafting an AAAI author response (rebuttal) under the single short character-limited author-feedback window, the no-URL rule, no-new-results guidance, AI-generated-review handling, and the AAAI two-phase review process where Phase-2 papers receive one feedback round before SPC/AC discussion.
日本語の概要は準備中です。原文の説明を表示しています。
Use when drafting an AAMAS rebuttal to preliminary OpenReview reviews, covering the double-blind constraint, the no-new-results and no-revised-paper norms, how to answer game-theory, MARL, and systems reviewers at once, and how to give the area chair a clean acceptance rationale within a short response window.
日本語の概要は準備中です。原文の説明を表示しています。
Stitch video segments with ffmpeg concat, xfade, overlay, audio mux, and export settings, and trim a source into named clips at exact windows (trim_clips.py). Ships montage.py, a free montage assembler (python3 + ffmpeg, no keys). It takes a JSON EDL of clips and stills, normalizes them and hard-cuts them in order, burns captions from an SRT, a cue list or word timings, and lays a VO over a music bed that ducks under it, mastered to -14 LUFS.
日本語の概要は準備中です。原文の説明を表示しています。
Hyperlocal weather data - precipitation, temperature, wind, soil moisture and more
日本語の概要は準備中です。原文の説明を表示しています。
Creates beautiful, branded HTML content assets — industry reports, landing pages, comparison sheets, one-pagers — from structured data. Uses Gamma API (preferred), v0.dev Platform API, or a self-hosted HTML template system with Tailwind CSS. Outputs self-contained HTML files that can be hosted as web pages or converted to PDF.
日本語の概要は準備中です。原文の説明を表示しています。
Assemble a whiteboard explainer video ad from a beats file — a narrator explains one idea while a real whiteboard fills up in black marker, with a hand-lettered title, bulleted rows down the left, a drawing filling the right, and a payoff that letters the closing line and rings the claim. The board is a PHOTOGRAPH and the ink is multiplied onto it, so the surface sheen and window light come through the strokes; the drawings are generated as line art and traced to ordered strokes, then revealed in drawing order on the word they belong to. The layout is SOLVED from the beats, never hand-placed. FREE assembly (Pillow plus ffmpeg) apart from one board photo and one drawing per subject, both one-time per brand. Use for the whiteboard format.
日本語の概要は準備中です。原文の説明を表示しています。
the UGC fix-loop toolkit — surgically re-render a bad window/beat of a single-take UGC master (stitch_replacement.py, pure FFmpeg) and GPT cross-model review a Seedance prompt before render (vet_seedance_prompt.py, routed through the openai-proxy). Fetch it into a one-shot UGC recipe so both scripts resolve on any machine and the vet call bills the Ads agent.
日本語の概要は準備中です。原文の説明を表示しています。
Assemble a narrated-UGC "stitch reply" ad from a config — a single spoken VO carries a verbatim testimonial while ~30 per-cut i2v clips (one creator across ~5 wardrobes in ~3 worlds, plus product B-roll) are each trimmed to their EDL window built from the VO's Whisper word boundaries and hard-concatenated via filter_complex concat (never the demuxer, which drops audio on a duration mismatch), the VO mixed over an optional sidechain-ducked instrumental bed (−20dB, 20 to 1) so the VO stays on top, karaoke-pop captions burned on every word throughout (VEED Whisper preset, re-spelled against the locked script), a landing-page scroll rendered as FFmpeg zoompan over a Playwright PNG (not i2v), and closed on the brand's real end-card PNG — never AI-rendered text. This is the FREE deterministic assembly stage (trim-to-EDL + filter_complex concat + VO and music mix + karaoke captions + landing-page zoompan + end-card append), run with the shared stitch-videos-ffmpeg montage.py helper that installs with this package; the VO, creator, start-frames, and clips come from create-vo-elevenlabs / create-image-gpt-image-fal / create-image-fal / create-video-fal. Use for the narrated-ugc-wardrobe-stitch format.
日本語の概要は準備中です。原文の説明を表示しています。
Answer questions about a brand's Meta ads (spend, results, which ad is winning, is it paused, why did Goose do that) only from reads made in the same turn, with the data window and sync time on every number and a plain caveat when the connection is stale or partial. Use it whenever a user asks how their ads are doing or why an ad action was taken.
日本語の概要は準備中です。原文の説明を表示しています。
Watch a brand's own product footage (screen recording, product film), pick the moment that proves each line with the user, and render those picks as a product layer — free, local. survey.py turns footage into timestamped contact sheets + scene cuts + motion so the agent can actually look at it; the agent writes a cut list (beat → source window + framing); preview.py draws it as a review sheet the user corrects round by round; cut.py renders the approved list into a silent 1080x1920 layer with the creator's area left as a plate. Also frames footage as a filmed screen (keystone, bezel, handheld drift) with dissolves between beats, and takes still screenshots as sources. Use for any format that shows real product footage beside, between or instead of a creator (split-screen, screen inserts, walkthroughs).
日本語の概要は準備中です。原文の説明を表示しています。
Assemble an animated character-explainer video ad (any art style — Pixar-style 3D, claymation, anime, paper-cut, felt) (~77s, 9:16) built on an "N types of X" listicle spine — a recurring human protagonist plus a locked cast of N persona characters, one per list item. Given the per-scene i2v clips + a per-scene target-duration table + a narration track, it trims each clip to its scene window, re-encodes every segment to identical 1080x1920/30fps/libx264/yuv420p (decrease+pad, never crop) so the concat demuxer never drops frames, concats, and muxes audio — in RESTYLE mode the source ad's VO+music mix is reused verbatim, in ORIGINAL mode fresh per-scene VO (loudnorm I=-14) is mixed under an optional music bed (loudnorm I=-26). A static-still fallback loops a scene's keyframe when its clip is missing/failed, so the master always assembles; libass captions are burned last. FREE deterministic assembly (Python + ffmpeg, no bash, no paid calls); the recipe supplies the clips, keyframes, VO or source audio, and caption table and gates the paid cast-anchor/keyframe/Kling-i2v/VO/music calls to their own capabilities. Use for the 3d-character-explainer listicle format.
日本語の概要は準備中です。原文の説明を表示しています。