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概要と使いどころ
Researches a company from its URL and produces a Brand DNA file covering positioning, audience, competitors, voice, and messaging. Use when starting work with a new brand or customer.
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Use when the user wants to pull data out of one or more PDFs (invoices, bank/credit-card statements, receipts, reports, tables) and put it into a spreadsheet. pdf_read is one of the most-used tools; this codifies the read-PDF → structure → write-Excel workflow. 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。
Maps intelligence for local SEO — geo-grid rank tracking, GBP profile auditing via API, review intelligence across Google/Tripadvisor/Trustpilot, cross-platform NAP verification (Google/Bing/Apple/OSM), competitor radius mapping, and LocalBusiness schema generation from API data. Three-tier capability: free (Overpass + Geoapify), DataForSEO (full intelligence), DataForSEO + Google (maximum coverage). Use when user says "maps", "geo-grid", "rank tracking", "GBP audit", "review velocity", "competitor radius", "maps analysis", "local rank tracking", "Share of Local Voice", or "SoLV".
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。
Reorganize the user's X and LinkedIn network with review-first pruning, add/follow recommendations, and channel-specific warm outreach drafted in the user's real voice. Use when the user wants to clean up following lists, grow toward current priorities, or rebalance a social graph around higher-signal relationships.
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。
Autonomous content pipeline - scout announcements in your field, triage by trend momentum and personal angle, produce posts/blogs/videos in your voice with ledger-based dedup, hard volume caps, and screenshot-verified publishing
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。
Edit drafts into sharper, more human writing while preserving the writer's personal voice, or detect AI-slop patterns without rewriting. Use when the user wants a draft clearer, more direct, more opinionated, or less AI-sounding, or asks whether writing reads as AI. Also the default writing standard for all agent output: 80% ASD-STE100 controlled language plus the format ladder (prose, diagram, HTML page, explainer video).
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。
Edit drafts into sharper, more human writing while preserving the writer's personal voice, or detect AI-slop patterns without rewriting. Use when the user wants a draft clearer, more direct, more opinionated, or less AI-sounding, or asks whether writing reads as AI.
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 full-manuscript prose and narrative craft on an Administrative Science Quarterly (ASQ) manuscript — voice, structure, and the storytelling ASQ is known for. Polishes the writing; it does not change the theory or analysis.
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 polishing the prose and structure of an Academy of Management Review (AMR) manuscript to AOM house style and an argument-driven voice. Late-stage polish; it does NOT build theory or check logic — do those first with amr-theory-development and amr-data-analysis.
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 full-manuscript prose polish of an Academy of Management Journal (AMJ) manuscript — front-loading the argument, active voice, structure, and AOM house style. Polishes language and structure; it does not create the theoretical contribution (amj-contribution-framing) or fix the analysis (amj-data-analysis).
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 revising an Academy of Management Annals (Annals) review for the house voice — authoritative, integrative, agenda-setting "reviews with an attitude," with a strong problem-first opening and a contribution-stating abstract. Polishes prose and structure; it does not design the framework (amann-organizing-framework) or run the submission preflight (amann-submission).
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。
Mandatory pre-publish review gate for a UGC video render. Transcribes the finished render's AUDIO with Whisper and word-diffs it against the approved spoken script, then gates pinning the final render (video_project_upsert patch.final_render_id) — blocking a render whose generated audio mis-voices a word (e.g. the approved "human-vetted" spoken as "human witted"), says a different number or brand name, flips a negation, drops an approved phrase, or comes back silent. Correct speech written differently ("5mg" said "five milligrams", "30%" said "thirty percent", a spoken URL, "don't" said "do not", "braxleybands" said "braxley bands", a confirmed pronunciation like "AG1" said "A G one") passes. Runnable, gating counterpart to content-goose's review-transcript-integrity atom. Every ugc-video-formats recipe runs this after render and BEFORE pinning the final render.
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。
End-to-end composite that turns a single brief into voice-tuned X post variants, LinkedIn post variants, and a matching social graphic. Orchestrates create-x-content + create-linkedin-content + goose-graphics in one invocation. Asks about graphic format when not specified, with heuristic-driven recommendations.
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。
Mine comments and replies on social posts, videos, and ads for recurring customer language, questions, objections, desired outcomes, complaints, product requests, purchase signals, and creative opportunities. Use for voice-of-customer research grounded in linked source evidence.
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。
Crawl a website's sitemap and blog index to build a complete content inventory. Lists every page with URL, title, publish date, content type, and topic cluster. Groups content by category and topic. Optionally deep-reads top N pages for quality analysis and funnel stage tagging. Use before SEO audits, content gap analysis, or brand voice extraction.
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。
Aggregate customer feedback from multiple sources — support tickets, NPS comments, Slack messages, G2 reviews, call transcripts, survey responses — into a unified VoC report with theme clustering, sentiment analysis, trend detection, and actionable recommendations for product, marketing, and CS teams. Chains review-site-scraper for public review 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。
Assemble a narrated motion-graphic LISTICLE video ad from a config — a spoken voiceover (cloned or cast, in the chosen tone) carries a numbered listicle while N web-animated hyperframe beats (HTML plus the Web Animations API, one branded design system of alternating tiles, big hero numerals, and callouts in the chosen visual style) are rendered frame-by-frame via Playwright and anchored to the VO's word-level timestamps, optional color-graded breather windows (brand clip, AI clip, or motion-graphic) give visual breath, and captions burn ONLY inside those B-roll windows (2-word chunks, ASS Format header carrying a Name field so none drop) with the VO mixed under a low music bed. This is the FREE deterministic assembly stage (Playwright beat render plus ffmpeg concat plus window-masked caption burn plus VO-and-music mix plus final composite) — the VO, the music bed, and any AI breather clips come from create-vo-elevenlabs, create-music-elevenlabs, and create-video-fal. Use for the vo-anchored-motion-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。
Research a company or brand from its website and produce a reusable Brand Core covering products, audience, competitors, positioning, offers, messaging evidence, voice, and visual identity. Use before growth, ad, content, creator, or product work when reliable brand context is missing.
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 the FREE steps of the flat-vector-explainer video format — a flat-illustration host character (who, where, tone, voice and music come from the recipe choices) walks a countable N-step product routine, one step per beat, and Remotion composites every chip/numeral/tagline/slate/CTA as an animated DOM overlay ON TOP of the Kling i2v character clips (text is NEVER baked into a keyframe — i2v warps type), the closing 'N products' grid is a PIL composite of the REAL product photos (not AI), full-sentence VO drives word-by-word burned captions over a VO-forward music bed, and the ~50s animated silent master is re-cut to a 30s deliverable FROM the animated master (never a static intermediate). Documentation-grade — ships config.example.json + PIPELINE.md + a README of the free assembly; the paid gen steps (keyframes, Kling i2v, VO, music) are separate capabilities the recipe orchestrates. Use for the flat-vector-explainer 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。
Assemble a song-driven music-video ad from a config — a generated sung track carries the whole narration across N tableaux (one keyframe -> one i2v clip per lyric beat) with NO separate voiceover, captions synced to the song's OWN word timings (script-window, never Whisper) and the hook word landing on the chorus drop, closed on a PIL brand end card. This is the FREE deterministic assembly stage (clip cut-to-timeline + captions + end card + FFmpeg composite); the song, keyframes, and clips come from create-music-elevenlabs / create-image-fal / create-video-fal. Use for the song-driven-music-video 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。
Assemble a multi-scene GRWM beauty-demo ad from a config — a locked-identity creator applies ~5 products step by step while a SEPARATE ElevenLabs voiceover narrates and every scene cut is snapped to the VO's product-name word-starts (Whisper word-level timestamps), then ~5 Playwright product overlay cards (real PDP-verified taglines) are composited onto the master each on its product-NAME word-start, the SEPARATE VO is mixed on top of a ducked music bed at loudnorm I=-14, clean-white 3-words/cue captions are burned, and the video closes on a flat-lay end card. This is the FREE deterministic assembly stage (re-cut to the VO word-starts, hard-concat, Playwright card render + card composite, VO plus music mix, caption burn, flat-lay end card); the VO, scene clips, product cutouts, and music come from create-music-elevenlabs / create-image-gpt-image-fal / create-video-fal. Use for the glassy-matte-grwm 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。
Generate an AI creator talking to camera, saying an approved script, as one continuous track — H3 Max reference-to-video through the GooseWorks fal-proxy (bills the Ads agent). Plans takes on line boundaries under H3's 15s cap, dry-runs a cost estimate, generates the first take alone so its voice can be locked and passed to every later take, joins takes with measured 0.10s dissolves, and moves each line's timing onto the words actually spoken. Use for any format with a generated creator speaking a script (split-screen, screen inserts, talking-head ads).
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。
Burned-in captions for a finished vertical video, three kinds. transcribe.py gets word timings from the video's own audio through the GooseWorks proxy (fal Whisper, bills the Ads agent, cents); captions.py burns one to three words at a time with Pillow + ffmpeg (no libass needed), either pinned to a split-screen seam (plate 25% above / 75% below) or at a fixed height, in a plate, outline or one-word serif style, with an optional red hook card; plates.py burns per-beat caption blocks (black, one union silhouette, placed in the emptiest band) for formats with no voice. The last caption (the CTA) holds to the final frame. Use as the last step of any video ad.
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。
Render the logo-equation card ad (7s, 9:16) — partner icon + brand icon joined by a plus sign as an equation, a two-line "= outcome" headline, four numbered steps, and a CTA that hard-cuts in at 2s, on a static black card over timelapse b-roll, no voice. render_card.py draws the two card plates with measured geometry and hard guardrails (the user must confirm the integration is real, no partnership/endorsement/ranking words, no comment-bait CTA, no dashes); compose.py lays the card over the b-roll sped up to read as a timelapse, with an optional bed; measure_motion.py gates the b-roll (a real-time shot reads as a photo). Free, local.
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。