Skip to main content

content-fanout

Adapt one canonical technical source into reviewed drafts for explicitly named connected channels, publish only selected targets, and collect verified URLs with channel attribution.

Datos de origen

Repositorio
AceDataCloud/Skills
Última actividad en el origen
5 de octubre de 2026 a las 17:09
Idioma detectado de SKILL.md
inglés
Estrellas
17
Forks
1

Opciones de instalación

De forma predeterminada está seleccionado el prompt que primero revisa el origen. Puedes cambiar a un comando directo o descargar una copia local.

Revisa los archivos de origen

Lee SKILL.md y los archivos complementarios que muestra SkillsMP antes de decidir si quieres instalarlo.

Mostrando SKILL.md

SKILL.md
Instrucciones de origen · Vista previa de solo lectura
name
content-fanout
description
Adapt one canonical technical source into reviewed drafts for explicitly named connected channels, publish only selected targets, and collect verified URLs with channel attribution.
when_to_use
Use when the user supplies a source article or release and names at least two target channels. This is a supervised distribution workflow, not a scheduled mass-posting service.
allowed_tools
["Bash","publish_artifact"]
license
Apache-2.0
metadata
{"author":"acedatacloud","version":"1.0"}
# Supervised content fan-out ## Inputs Require a canonical source URL or complete source text, a campaign ID, and an **explicit** target list. Never expand `all platforms` into every connector. Read the conversation's authoritative `<connectors>` and `<skills>` blocks to identify active publishing skills. For an unconnected target, list its connection link and leave it pending; never guess a skill slug or call an unconnected loader. ## Prepare 1. Extract verifiable claims, links, media rights, product availability, and a single canonical destination. Drop unsupported performance claims. 2. Produce a channel-specific draft and an attributed link for each target: `utm_source=<channel>&utm_medium=<medium>&utm_campaign=<campaign>`. Use `social` for social/community posts and `referral` for developer directories and syndicated technical articles; use the campaign contract's registered source mapping when one exists. Preserve any existing query parameters. Keep a separate draft for each language and audience; do not copy an identical body everywhere. 3. Present a table with target account, title, complete text, link, attachment, and proposed visibility. Ask the user to select exact targets and review the final drafts before public writes. ## Publish and verify Load each target's existing skill one at a time and follow its own official API, confirmation, and readback rules. A loaded skill can narrow the active tool set; `load_skill` remains available for switching. Send one target at a time and record the returned ID or URL. On timeout, 5xx, or ambiguous result, read the target account's recent posts before any retry. Do not issue a second write merely because the first response was lost. Use `publish_artifact` once for each **verified** public URL. Report these states separately: `draft`, `submitted`, `verified`, `failed`, and `pending`. This workflow has no durable cross-run dedup database, so it must stay supervised; a scheduled service must add persistent `source_id + channel + content_hash` idempotency before unattended use. For Reddit, Hacker News, Product Hunt, and Habr, prepare platform-native drafts for manual review. Do not automate community submissions or bypass platform publication rules. For LinkedIn, X, TikTok, Instagram, and other reviewed APIs, public automation is available only after the actual app permissions are active and the target skill proves a verified result.
Ver en GitHub