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Content-reactive audience profiling, platform-specific style cards, creator style analysis, topic cluster mapping, and creator-owned winning content profiles
デフォルトでは、最初にソースを確認する Prompt が選択されています。直接コマンドに切り替えるか、ローカルコピーをダウンロードすることもできます。
インストールを決める前に、SKILL.md と SkillsMP に表示されている付属ファイルをお読みください。
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
直接コマンドでは確認用 Prompt が省略されます。実行前にソースを確認してください。
npx skills add https://github.com/Farrice/mes-knowledge-base --skill kieran-flanagan-audience-intelligenceコマンドは1行のまま表示されます。コピー前に横へスクロールして全体を確認してください。
ローカルで確認しますか？SkillsMP が現在取得できるファイルをダウンロードできます。
SKILL.md を表示中
| name | Kieran Flanagan - Audience Intelligence |
| description | Content-reactive audience profiling, platform-specific style cards, creator style analysis, topic cluster mapping, and creator-owned winning content profiles |
| version | 1.1 |
| format | completion-engine |
| workflows | 5 |
| routing | long-tail |
The foundation layer of Kieran's AI content team architecture. These research and profiling tools create the intelligence that informs ALL content creation — they pair with any content creation skill in the system, not just Kieran's content engine.
| # | Workflow | Produces | Use When |
|---|---|---|---|
| 01 | Content Audience Profile | A content-reactive audience profile built from real engagement data | You need to understand WHO responds to your content — not a theoretical ICP, but a living profile based on what actually resonates |
| 02 | Content Style Card | Platform-specific writing style card with vocabulary library | You need to capture a creator's voice on a specific platform — LinkedIn style ≠ newsletter style ≠ X style |
| 03 | Style From Creator | Writing style card reverse-engineered from any public creator | You want to learn from or model another creator's style, or you haven't created enough content to build your own style card |
| 04 | Content Cluster | Topic cluster analysis with performance mapping and gap identification | You want to see which topics drive the most engagement, which are underexplored, and where to double down |
| 05 | Winning Content Profile | Versioned platform-specific profile of transferable creator-owned patterns | You need to map new ideas to patterns that have worked for this creator on one platform |
5 deterministic practitioner prompts — each carries an Output Contract, Output Skeleton, and Quality Gate. When a deliverable matches one, Read it and honor its contract instead of improvising the output shape.
skills/kieran-flanagan-audience-intelligence/references/prompts-v2/content-audience-profile.mdskills/kieran-flanagan-audience-intelligence/references/prompts-v2/content-cluster.mdskills/kieran-flanagan-audience-intelligence/references/prompts-v2/content-style-card.mdskills/kieran-flanagan-audience-intelligence/references/prompts-v2/style-from-creator.mdskills/kieran-flanagan-audience-intelligence/references/prompts-v2/winning-content-profile.mdThe /generate front door — in-house, pay-as-you-go creative generation (Higgsfield replacement). One command for image, video, and audio: routes each request to the right model recipe (skills/generate/models/*.json), defers to binding creative_router lanes (people → fal-people, style-family → fantastic-posters; Higgsfield fully retired 2026-08-06), quotes paid video before running, honors prompt-level budgets ("total budget $3"), runs comparison batches across models, logs every prompt beside its asset, and auto-refreshes the Asset Command Center (/assets-board). Use when the user says "generate", "make an image/video/voiceover", "create ads/assets/creative", names a model (recraft, kling, seedance, nano banana, gpt image), or asks for a multi-model comparison. Source: RoboNuggets 9C4TRbucmhQ, rebuilt on our fal-first stack.
The Edit Bay — in-house conversational video studio (VOX-style explainers, documentaries, shorts, LinkedIn video). Transcript-driven cutting, B-roll ladder, motion graphics as code, captions, music, publish-ready packages — all agent-operated, free-first. Use when Farrice says "edit this video/footage", "make an explainer/documentary/short", "cut this recording", "add B-roll/captions/music", "turn this essay/post into a video", or any video production ask. Front door for three modes: talking-head, VO-only, zero-camera (his recorded VO + assembled visuals — NO voice clone, NO TTS narration, his ruling 2026-08-06). Source: Brad Bonanno agentic edit pipeline (extractions/brad-bonanno-edit-bay/), rebuilt on the house stack: WhisperX local + edit_bay.py ffmpeg assembly + HyperFrames/Remotion graphics + /generate (fal) — NO Higgsfield (retired 2026-08-06).
Architects technical explainer videos using Brad Bonanno's structural patterns — survives short attention spans, communicates complete systems (not just teasers), and functions as a channel-building artifact (one video pulls subscribers, not just views). Use when planning a long-form technical explainer (5-20 min) for YouTube, structuring an explanation of a complex system the user knows but can't teach yet, balancing depth vs accessibility for a technical audience, or building an evergreen video meant to compound subscriber growth over years rather than spike then die. Trigger proactively whenever the user says "explainer video", "technical explainer", "how do I explain X", "long-form YouTube", "evergreen video", or has a complex system that needs to land with a non-expert. For Instagram-format shareworthy content use brock-johnson-shareworthy-content; for short-form video patterns use a TikTok/Reels-specific skill.
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