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dropspace-content-engine

Name: dropspace-content-engine
Author: jclvsh

作者 JCLVSH · GitHub ↗ · v1.0.1 · MIT-0

cross-platform ✓ 安全检测通过

110

总下载

当前安装

版本数

在 OpenClaw 中安装

/install dropspace-content-engine

功能描述

Self-improving autonomous content pipeline. Analyzes post performance across 6 platforms, generates new content with AI (slideshows, tweets, linkedin posts,...

使用说明 (SKILL.md)

Dropspace Content Engine

Fully autonomous content pipeline. Every night: pull analytics → identify winning hooks → generate new posts → schedule across 6 platforms. The feedback loop compounds — each cycle produces better content because it learns from real engagement data.

Setup

1. Clone and install

git clone https://github.com/joshchoi4881/dropspace-agents && cd dropspace-agents && npm install

If canvas fails to install, that's fine — text-only formats still work. For visual formats (TikTok/Instagram slideshows): macOS brew install pkg-config cairo pango, Linux apt install libcairo2-dev libpango1.0-dev, then npm install again.

2. Run the setup wizard

node setup.js --template dropspace-content-engine

Walks you through API keys, platform selection, and app configuration.

3. Set your API keys

export DROPSPACE_API_KEY="ds_live_..."     # from dropspace.dev/settings/api
export ANTHROPIC_API_KEY="sk-ant-..."       # from console.anthropic.com
export FAL_KEY="fal_..."                    # from fal.ai (for visual/video formats)

Save in a .env file (copy from templates/.env.example). Add .env to .gitignore to avoid committing secrets.

4. Validate

node scripts/test-pipeline.js --app myapp

Run the Pipeline

source .env

# Analyze performance + generate new posts
node scripts/run-self-improve-all.js --app myapp

# Schedule generated posts for today
node scripts/schedule-day.js --app myapp

Automate Nightly

Time (ET)	Script	What
12:00 AM	`scripts/refresh-tracking.js --all` + `scripts/cleanup-posts.js --all`	Refresh analytics, clean old media
12:30 AM	`scripts/run-x-research.js --app myapp`	Scan X for trending hooks (optional, needs Bird CLI)
1:00 AM	`scripts/run-self-improve-all.js --app myapp`	Analyze + generate (up to 60 min)
2:00 AM	`scripts/schedule-day.js --app myapp`	Schedule for today

What Happens Each Run

Pulls 14 days of analytics from Dropspace API
Identifies winning hooks (posts with >2x average engagement)
Cross-references with X/Twitter research signals
Generates 7-14 new posts with AI (text, visual, video formats)
Fact-checks any claims about people, products, or events
Writes strategy notes that persist between runs (the loop compounds)
Schedules posts across the day via Dropspace API

Content Formats

Format	Type	Platforms
story-slideshow	visual	TikTok, Instagram, Facebook
ugc-reaction	video	TikTok, Instagram
text-single	text	Twitter/X
text-post	text	LinkedIn, Reddit, Facebook

Links

Community page: https://www.dropspace.dev/community/dropspace-content-engine
Case study: https://www.dropspace.dev/case-studies/march-2026
Repo: https://github.com/joshchoi4881/dropspace-agents
Dropspace API docs: https://www.dropspace.dev/docs

安全使用建议

This skill appears to do what it claims, but take the usual precautions before running code that will post content and hold API keys: 1) Inspect the GitHub repo (particularly package.json, setup.js, and scripts/) for postinstall scripts or unexpected network actions before running npm install. 2) Run initial tests with limited-scope or test accounts (so posts won't go to your main social accounts). 3) Restrict and rotate API keys you provide (use short-lived or scoped credentials if possible). 4) Keep .env out of source control as recommended. 5) Be aware the setup may prompt for additional platform tokens (not listed in registry metadata) and optional tooling like the Bird CLI will need separate credentials.

功能分析

Type: OpenClaw Skill Name: dropspace-content-engine Version: 1.0.1 The skill defines an autonomous social media content pipeline that integrates with the Dropspace API, Anthropic, and Fal.ai. It requires cloning an external GitHub repository (joshchoi4881/dropspace-agents) and installing standard Node.js dependencies. The instructions in SKILL.md are consistent with the stated purpose of multi-platform automation and include appropriate security advice, such as using .gitignore for environment variables, with no evidence of malicious intent or prompt injection.

能力评估

✓ Purpose & Capability

Name and description (autonomous multi-platform content pipeline) align with the declared env vars (DROPSPACE_API_KEY for the Dropspace API, ANTHROPIC_API_KEY for LLM-assisted generation, FAL_KEY for visual/video generation) and the SKILL.md commands that call scripts to analyze, generate, and schedule content.

ℹ Instruction Scope

SKILL.md instructs cloning the repo, running npm install, running setup.js to provide API keys/platform selection, and executing node scripts that pull analytics and schedule posts via Dropspace. This stays within the described purpose. One notable point: the setup likely collects platform-specific credentials (for scheduling to third‑party platforms) but those platform tokens are not enumerated in requires.env; the SKILL.md also references an optional 'Bird CLI' run for X/Twitter research which would require separate credentials if used.

ℹ Install Mechanism

No formal install spec in the registry, but SKILL.md instructs 'git clone https://github.com/joshchoi4881/dropspace-agents && npm install'. Clone from GitHub is expected for a project-based skill, but npm install will execute code from the repo and its dependencies (including any postinstall scripts). It's standard but worth reviewing the repo and package.json before running in production.

ℹ Credentials

The three required env vars map to expected services (Dropspace, Anthropic, Fal). However, the setup likely requests additional platform credentials (social accounts, scheduler tokens) which are not listed in requires.env — you should expect the .env produced by setup to contain extra secrets. Ensure those are scoped appropriately and not reused elsewhere.

✓ Persistence & Privilege

The skill is not always-enabled and does not request elevated platform privileges in the registry metadata. It instructs creating/storing a .env file for keys (normal for app setup) and does not attempt to modify other skills or system-wide agent settings.

如何使用

确保已安装 OpenClaw（本地或 Docker 部署）
在对话框中输入安装命令：/install dropspace-content-engine
安装完成后，直接呼叫该 Skill 的名称或使用 /dropspace-content-engine 触发
根据 Skill 的参数说明提供必要输入，即可获得结构化输出

版本历史

v1.0.1

- Initial release of dropspace-content-engine. - Fully autonomous content pipeline: analyzes engagement data, generates new posts, and schedules across 6 platforms. - Learns and self-improves nightly based on real engagement analytics. - Supports multiple content formats including visual slideshows, tweets, Reddit threads, LinkedIn posts, and short-form video reactions. - Easy setup via CLI wizard and .env configuration for API keys. - Includes scripts for scheduled analytics refresh, content generation, and multi-platform posting automation.

v1.0.0

Initial release: Autonomous engine for cross-platform content creation and scheduling. - Analyzes post performance across 6 major platforms nightly. - Generates and schedules new AI-powered content (text, slideshows, video, UGC reactions) based on real engagement data. - Automated feedback loop: each cycle adapts and improves content strategy. - Setup wizard for API keys, platform selection, and configuration. - Includes automation scripts for end-to-end pipeline and scheduling. - Supports modular post formats for X/Twitter, LinkedIn, Reddit, TikTok, Instagram, and Facebook.

元数据

Slug dropspace-content-engine

版本 1.0.1

许可证 MIT-0

累计安装 0

当前安装数 0

历史版本数 2

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