Social Scheduler
Una settimana di post in linea con il brand, programmati ovunque, prima approvati.
Trasforma i tuoi argomenti in una settimana di post in linea con il brand su ogni piattaforma — tu approvi ogni post prima che venga pubblicato.

Installala in 3 passaggi
Nessuna registrazione. Nessuno strumento da riga di comando. Scegli la tua AI, copia una riga e incollala.
Preferisci fare da te? Acquista la skill ($4.99), scarica lo ZIP dalla conferma d'acquisto, decomprimilo nella cartella mostrata sopra e riavvia la sessione della tua AI — stesso risultato. L'hai già acquistata? Il tuo assistente AI può scaricarla per te.
Prove dal mondo reale
Persone vere hanno svolto proprio questo lavoro con agenti IA.
Create, schedule and post content across platforms automatically
Leggi il caso →Caso d'usoCreate and schedule social content through Blotato
Leggi il caso →Cosa contiene
Un file SKILL.md (la guida operativa) + un modello di partenza. Un'anteprima:
Social Scheduler
When to use
- You post inconsistently because drafting each post takes too long
- You want LinkedIn, X, and YouTube covered without writing three versions of everything
- Your social presence drifts off-brand whenever you're busy
- Repurposing (video → carousel, article → thread) never actually happens
- You want one approval session per week to produce the whole week's calendar
Workflow
- Set the voice (input: brand guide + best past posts → output: voice file)
Write a voice file the agent reads on every run: who you are, how you sound, words you never use, and 5–10 of your best past posts as examples. Then write one platform-rules file: format limits, tone shifts, and posting norms per platform. Garbage in, generic out — this file is the quality control. - Feed the topics (input: topics / trend feed / one video → output: content brief)
Give the agent the week's raw material: a list of topics, a trend feed (e.g. YouTube trends), or one long piece to repurpose. One instruction should be enough to pull the trends and draft everything — the brief stays short: topic, angle, target platform mix. - Draft the batch (input: brief + voice file → output: platform-ready drafts)
Draft each idea in its platform's shape: a LinkedIn post plus infographic, a video script turned into a carousel, a thread cut from an article. Follow the voice file for tone and the platform-rules file for format. Media the AI generates (video, images, edits) gets a cost check first — generation is metered, so budget per post before scaling. - Preview everything (input: drafts → output: approval sheet)
Drafts land in one shared sheet or notes view with the full week's schedule: post, platform, format, publish time. Nothing schedules itself at this stage. You read every word and see every image before it goes anywhere. - Approve and schedule (input: approved drafts → output: published queue)
Approve, edit, or skip each post. Approved posts schedule across all platforms in one pass through a scheduling tool (e.g. Blotato). Publish is never automatic: every post carries your explicit approval, which keeps you compliant with platform API policies and account-safety rules. - Learn the loop (input: performance log → output: updated pillars)
Log performance per post (reach, engagement) and review weekly. Feed the learnings back into your content pillars and the voice file — the good ideas repeat, the flops get retired. Update the platform-rules file when a platform changes its policies or formats.
Output spec
Anteprima del modello
Social Scheduler — Voice File & Weekly Batch Template
Two pages. Fill the voice file once (review quarterly); use the batch sheet every week.
Voice file (fill once)
Who we are: {one line, e.g. "B2B tool for small retailers"} Sound like: {e.g. "plain-spoken, practical, no hype"} Never sound like: {e.g. "guru, motivational, jargon-heavy"}
Banned phrases: {e.g. "as an AI", "revolutionize", "game-changer"}
3–5 example posts in our voice:
- {paste a past post that performed well}
- {another one}
- {another one}
Platform rules (fill once, update when policies change)
Content pillars: {e.g. "product tips", "customer stories", "industry takes"}
Il pacchetto della skill (SKILL.md + modello) è scritto in inglese.
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