菜单
AI-powered SEO operations: keyword intelligence, competitor gap analysis, Google Search Console optimization, and trend detection. Use when asked to research keywords, analyze competitor content gaps, audit GSC performance, or detect trending topics. For growth experiments see growth-engine; for content optimization see autoresearch.
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。
基于 SOC 职业分类
Use when adversarially reviewing a document that makes formal or technical claims — math derivations, physics papers, statistical analyses, benchmark reports, whitepapers. Inventories every equation and quantitative claim, verifies each AS NAMED in the text (never a paraphrase or a neighboring statement), and classifies VERIFIED / REFUTED / UNVERIFIABLE / VACUOUS. Triggers on "check this paper", "verify these claims", "is this derivation right", "review this proof", "audit this benchmark", "does the math hold up". For source-code review see code-review-and-quality; for skill/agent library audits see skill-library-review; for content quality scoring see content-ops.
Run Karpathy-style autoresearch optimization on any content. Generates 50+ variants, scores with a 5-expert simulated panel, evolves winners through multiple rounds, outputs optimized version + full experiment log. Use when optimizing landing pages, email sequences, ad copy, headlines, form pages, CTA text, or any conversion-focused content. Triggers on "optimize this page", "run autoresearch", "score these variants", "A/B test this copy".
Tests in real browsers. Use when building or debugging anything that runs in a browser. Use when you need to inspect the DOM, capture console errors, analyze network requests, profile performance, or verify visual output with real runtime data via Chrome DevTools MCP.
Conducts multi-axis code review across correctness, readability, architecture, security, and performance. Use before merging any change. Use when reviewing code written by yourself, another agent, or a human. Triggers on "review my PR", "review this diff", "code review", "review this changeset", "is this ready to merge", "pre-merge review".
Estimate the full development cost of an existing codebase from lines of code, architectural complexity, and team-composition overhead. Use for 'how much would this cost to build', 'what did this codebase cost', development-cost or build-cost estimates, calendar-time estimates, and Claude/AI ROI on a delivered codebase. Estimates by measured LOC and complexity, not by ticket volume.
Auto-assembles a domain-specific expert panel (7–10 experts), scores any content or strategy artifact against a typed rubric, and iterates until the aggregate hits 90+ (max 3 rounds). Use as a quality gate on copy, email sequences, landing-page drafts, strategy docs, charts, titles, or recruiting evaluations — or when another skill needs a final review gate on its output. Triggers on "expert panel this", "score this", "rate these variants", "quality check this", "panel review", "expert score", "evaluate this copy/strategy/page". For variant generation and multi-round conversion optimization see autoresearch; for live-URL CRO auditing see conversion-ops; for the scripted content-production pipeline see content-pipeline.
| name | seo-ops |
| description | AI-powered SEO operations: keyword intelligence, competitor gap analysis, Google Search Console optimization, and trend detection. Use when asked to research keywords, analyze competitor content gaps, audit GSC performance, or detect trending topics. For growth experiments see growth-engine; for content optimization see autoresearch. |
| when_to_use | Use when performing keyword research or generating a content brief, finding quick-win striking-distance keywords from Google Search Console, running a competitor content gap analysis, detecting trending topics for content creation, identifying decaying pages with traffic drops, or building a prioritized keyword target list scored by Impact × Confidence. Not when: running growth experiments or A/B tests — use growth-engine instead. Not when the content-gap analysis is REVENUE/pipeline-driven (which content drives deals or revenue, buyer-journey gaps) rather than SEO/search-driven — use revenue-intelligence; this skill's gap analysis is keyword/search-demand-driven. For deep content research and optimization use [autoresearch](../autoresearch/SKILL.md). |
| compatibility | Requires Bash (Python 3 where scripts are invoked). Works in Claude Code and Codex via install.sh. |
AI-powered SEO operations: keyword intelligence, competitor gap analysis, GSC optimization, and trend detection.
| Tool | Purpose |
|---|---|
scripts/content_attack_brief.py | Full keyword intelligence pipeline: BOFU keywords, competitor gaps, decaying pages |
scripts/gsc_client.py | Google Search Console API client (CLI + library) |
scripts/gsc_auth.py | One-time OAuth setup for GSC access |
scripts/trend_scout.py | Multi-source trend detection across Google Trends, HN, Reddit, X |
scripts/gsc_auth.py once before any GSC tool — it saves the OAuth token locally.