Super Marketing Pro

核心功能为全链路B2B营销执行，需先生成ICP（理想客户画像），再完成多平台内容矩阵打造、SEO策略、冷邮件序列、竞品战报、内容复用及营销报告等任务。适用于B2B企业全流程营销需求，输入为行业、产品参数或文件，输出各类营销资产、报表等，覆盖中外主流平台。

wd041216-bit

热度 51.38

最近更新 2026-05-11 17:33:02

分类：营销依赖：代码执行 / 读写文件 / 第三方 API应用场景：文案创作 / 社交媒体 / 市场分析 / 报告撰写 ...

安装技能

复制下面的话术发给你的 Agent，它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill： npx secure-skills-cli add super-marketing-pro

Metadata

name: super-marketing-pro
description: Full-stack B2B marketing execution skill equivalent to a 10-person agency team. Use for: building ICP and brand messaging, generating multi-platform content matrices, writing cold email sequences, SEO topic cluster strategy, competitor battle cards, content repurposing (1 long-form → LinkedIn/X/TikTok/Xiaohongshu), and monthly/quarterly marketing reports. Covers Chinese platforms (抖音, 小红书, 微信) and Western platforms (LinkedIn, YouTube, Instagram, X). Triggers on: marketing strategy, social media content, SEO analysis, competitor research, email sequence, content calendar, hashtag, ICP, 营销策略, 社媒内容, 竞品分析, 内容日历, 邮件序列.

Super Marketing Pro

Full-stack B2B marketing skill. Always run strategy_builder.py first to define ICP before generating any content.

Golden Rule: Strategy First

Never generate copy without an ICP. The workflow is always: ICP → Content → Repurpose → Distribute → Monitor → Report

Scripts

All scripts are in scripts/. Run with python3. Requires openai package (pip3 install openai).

Script	Function	Key Args
`strategy_builder.py`	Generate ICP, messaging framework, elevator pitch	`--industry` `--product`
`content_repurposer.py`	1 long-form doc → multi-platform content matrix	`--source <file.md>` `--platforms`
`hashtag_generator.py`	Platform-specific hashtag matrix	`--content` `--platforms "linkedin,douyin,xiaohongshu"`
`content_calendar.py`	Weekly/monthly publishing schedule	`--months` `--output <file.csv>`
`email_sequence_generator.py`	5-stage cold email sequence	`--target` `--stages`
`seo_analyzer.py`	LLM-powered Topic Cluster strategy	`--seed-keyword` `--depth deep`
`competitor_monitor.py`	Batch competitor battle cards	`--batch-list <file.txt>` `--export-format json`
`data_reporter.py`	Multi-month cross-platform ROI report	`--type monthly` `--months 1,2,3`
`llm_utils.py`	Shared LLM utility (auto-imported)	—

llm_utils.py uses OPENAI_API_KEY env var. Default model: gemini-3.0-flash. Includes exponential backoff retry (3 attempts).

Execution Workflow

Stage 1 — Strategy: Run strategy_builder.py → get ICP, buyer personas, messaging pillars.

Stage 2 — Content Creation: Based on goal:

Awareness/SEO: Run seo_analyzer.py → write long-form pillar content.
Lead Gen: Read references/content_templates.md → write whitepaper or case study.
Outbound: Run email_sequence_generator.py.

Stage 3 — Repurpose: Run content_repurposer.py on any long-form asset → get LinkedIn post, X thread, TikTok/Douyin script, Xiaohongshu note.

Stage 4 — Distribute: Run hashtag_generator.py for tags, then content_calendar.py for scheduling.

Stage 5 — Convert: Run email_sequence_generator.py for lead nurturing sequences.

Stage 6 — Monitor & Report: Run competitor_monitor.py for battle cards, data_reporter.py for attribution reports.

Knowledge Base (References)

Load the relevant reference file before executing platform-specific tasks:

Strategy: abm_framework.md (ABM + sales alignment), messaging_icp_guide.md (ICP workshop), funnel_strategy.md (TOFU/MOFU/BOFU + attribution)

Channels: linkedin_guide.md, youtube_seo.md, douyin_algorithm.md, xiaohongshu_tips.md

Content: content_templates.md (whitepapers, case studies, emails), keyword_library.md (B2B keyword matrix)