briar-cochran-content-science

Data-backed ideation and content testing systems from Briar Cochran — the idea supply chain (five-input weekly ideation hour, Great Idea Venn gate, baseline-relative outlier detection, four-layer contextualization filter) plus the testing economy (Chris Rock arsenal loop at 4:3 winners-to-tests, four-question win audits building four arsenals, follower-quality economics). Use when generating content ideas from data instead of taste, deciding whether a competitor video is worth adapting, planning a weekly content slate, postmorteming why a post won, installing a repeatable content OS on any account, or scripting a keyword-cascade belonging piece. Upstream of hook/retention craft: this skill decides WHICH ideas enter production.

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Repositório: Farrice/mes-knowledge-base
Última atividade na origem: 25 de julho de 2026 às 16:15
Idioma detectado do SKILL.md: inglês
Estrelas: 0
Forks: 1

Opções de instalação

Por padrão, está selecionado o prompt que primeiro revisa a origem. Você pode mudar para um comando direto ou baixar uma cópia local.

Instalar com Codex ou Claude Copie este prompt, cole no Codex, Claude ou outro assistente e deixe que ele revise a página da skill e instale para você.

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npx skills add https://github.com/Farrice/mes-knowledge-base --skill briar-cochran-content-science

O comando permanece em uma só linha. Role horizontalmente para revisá-lo antes de copiar.

Prefere uma cópia local? Baixe os arquivos disponíveis atualmente no SkillsMP.

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24 arquivos

SKILL.md

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generate

The /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.

2026-08-06

video-studio

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).

2026-08-06

brad-bonanno-explainer-video-architecture

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.

2026-08-06

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name	briar-cochran-content-science
description	Data-backed ideation and content testing systems from Briar Cochran — the idea supply chain (five-input weekly ideation hour, Great Idea Venn gate, baseline-relative outlier detection, four-layer contextualization filter) plus the testing economy (Chris Rock arsenal loop at 4:3 winners-to-tests, four-question win audits building four arsenals, follower-quality economics). Use when generating content ideas from data instead of taste, deciding whether a competitor video is worth adapting, planning a weekly content slate, postmorteming why a post won, installing a repeatable content OS on any account, or scripting a keyword-cascade belonging piece. Upstream of hook/retention craft: this skill decides WHICH ideas enter production.
expert	Briar Cochran (@BriarCochranShortForm)
version	1.0.0
domain	content ideation, content testing, data-backed topics, audience economics
extraction_date	"2026-07-25T00:00:00.000Z"
extraction_tier	forge (Deep)
source_material	"Personal Brand Guide to Top 1% Ideation (data-backed)" (4aAQJ2jF-uc) + "Become A Content Scientist (Personal Branding)" (EO1SaBO-YTg) + "Importance of Follow Quality" (j5nSArMEFno, enrichment) — full transcripts + /watch visual context