searchintentautomation

Use when turning a niche, offer, product, or topic into a keyword map, audience question map, and an agent-executable workflow using Ubersuggest, AnswerThePublic, Playwright MCP browser capture, and Python orchestration. Also use when extracting repeatable market-research workflows from reels, demos, or creator tool stacks and rewriting them into non-interactive CLI-agent pipelines.

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仓库: Sheshiyer/skill-clusters
最近来源活动: 2026年6月5日 13:43
检测到的 SKILL.md 语言: 英语
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分支: 1

安装方式

默认使用会先检查来源的 Prompt；你也可以切换为直接命令，或下载本地副本。

用 Codex 或 Claude 帮你安装复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。

直接命令不会经过审查 Prompt；运行前请先检查来源。

npx skills add https://github.com/Sheshiyer/skill-clusters --skill searchintentautomation

命令会保持在同一行。复制前请横向滚动并检查完整内容。

想先保存到本地？可下载 SkillsMP 当前能够提供的文件。

检查来源文件

决定是否安装前，请先阅读 SKILL.md，以及 SkillsMP 当前展示的配套文件。

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8 个文件

SKILL.md

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arcplume

Arcplume runs Grok through the Grok Build CLI's own OAuth-authenticated session (grok login) for image generation, with strict preflight validation, secret-safe handling, and headless CLI-driven execution -- no separate XAI_API_KEY billing. Video falls back to the billed xAI API. USE WHEN a user wants to generate an image via a locally logged-in Grok Build CLI session, e.g. 'generate an image with grok', 'use grok build', or 'use my logged-in grok session'.

2026-07-07

selemene-core

Shared reference for the Selemene cluster: the two report surfaces (deterministic Rust reports vs. narrative witness-pipeline readings), the @selemene/bridge CLI contract, the output manifest format, and non-prescriptive witnessing tone. USE WHEN deciding which Selemene surface to invoke or when routing between birth/compatibility/transit reports and solo/dyadic readings.

2026-07-07

selemene-orchestrator

Route Selemene Engine tasks to the right surface: deterministic reports (birth/compatibility/transit) via selemene-core and the @selemene/bridge CLI, or narrative witness readings via selemene-report. USE WHEN the user wants anything under the Selemene/Noesis umbrella but has not named the exact surface.

2026-07-07

查看这个仓库的全部 Skills

SearchIntentAutomation

Turn a seed topic into an actionable research and automation workflow.

Workflow Routing

Trigger

Workflow

Extract a reusable workflow from a reel or creator demo

Workflows/ExtractFromSource.md

Build a keyword, question, and automation stack for a topic or offer

Workflows/BuildOpportunityMap.md

Run the workflow end-to-end with CLI coding agents

Workflows/RunWithCliAgents.md

Quick Reference

Step 1: Use Ubersuggest to map demand, keyword variants, SEO opportunities, and competitor gaps.

Step 2: Use AnswerThePublic to map real audience questions, comparisons, and prepositions around the same seed term.

Step 3: Use Playwright MCP to capture browser-only research data and a Python CLI pipeline to normalize, merge, and route outputs.

Step 3a: Hand off browser results with the capture manifest contract in Tools/CaptureStatusContract.md.

Step 4: Optional AI layer: generate content briefs or landing-page drafts from the validated keywords/questions.

If the pipeline gets stuck, stop and present a taxonomy-based checkpoint with:

Recommended option 1
Recommended option 2
Custom user direction

Loaded Context

Reel evidence and extraction trace: ReelEvidence.md

Core workflow details: Workflows/BuildOpportunityMap.md

Non-interactive agent execution: Workflows/RunWithCliAgents.md

Failure and checkpoint taxonomy: FailureTaxonomy.md

Playwright-to-Python handoff contract: Tools/CaptureStatusContract.md

SearchIntentAutomation

Turn a seed topic into an actionable research and automation workflow.

Workflow Routing

Trigger

Workflow

Extract a reusable workflow from a reel or creator demo

Workflows/ExtractFromSource.md

Build a keyword, question, and automation stack for a topic or offer

Workflows/BuildOpportunityMap.md

Run the workflow end-to-end with CLI coding agents

Workflows/RunWithCliAgents.md

Quick Reference

Step 1: Use Ubersuggest to map demand, keyword variants, SEO opportunities, and competitor gaps.

Step 2: Use AnswerThePublic to map real audience questions, comparisons, and prepositions around the same seed term.

Step 3: Use Playwright MCP to capture browser-only research data and a Python CLI pipeline to normalize, merge, and route outputs.

Step 3a: Hand off browser results with the capture manifest contract in Tools/CaptureStatusContract.md.

Step 4: Optional AI layer: generate content briefs or landing-page drafts from the validated keywords/questions.

If the pipeline gets stuck, stop and present a taxonomy-based checkpoint with:

Recommended option 1
Recommended option 2
Custom user direction

Loaded Context

Reel evidence and extraction trace: ReelEvidence.md

Core workflow details: Workflows/BuildOpportunityMap.md

Non-interactive agent execution: Workflows/RunWithCliAgents.md

Failure and checkpoint taxonomy: FailureTaxonomy.md

Playwright-to-Python handoff contract: Tools/CaptureStatusContract.md

searchintentautomation

安装方式

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