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every-app/open-seoチェック済み

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competitive-landscape

every-app/open-seo/competitive-landscape

Map SEO market leaders, winning content themes, keyword coverage, backlinks, and strategic gaps.

インストール · 120出典を見る

Installation

npx skills add https://github.com/every-app/open-seo --skill competitive-landscape

スキルファイル

SKILL.md

最終同期 · 2026/08/30

SKILL.md
---
name: competitive-landscape
description: Map SEO market leaders, winning content themes, keyword coverage, backlinks, and strategic gaps.
---

# OpenSEO Competitive Landscape

## Goal

Answer: "Who is winning this SEO market, what content is working for them, and where are the openings?"

Use this when the user wants a market-level view across several competitors. For a deep dive on one domain, use `competitor-analysis`.

## Required inputs

- `projectId`
- Topic, seed keywords, market/category, or user's domain
- Optional known competitors
- Optional location/language

## Project context

The project-context tools are free and shared with the app and other agents.

1. Call `get_project_context` first and ground the market read in it — the saved competitors are the starting roster, and the business and positioning decide who counts as a competitor.
2. This skill needs competitors. If none are saved, run a minimal inline setup: ask the user who they compete with, or infer a shortlist from `find_serp_competitors` and the site and confirm it, write it back with `update_project_context` (`addCompetitors`), then continue the landscape work. Never front-load the full interview; suggest `seo-project-setup` at the end for the rest.
3. Before spending credits, check the research log. If the same research ran within the last 30 days, reuse that result and say so instead of re-buying it.
4. On finish, write back what is durable with `update_project_context` — every confirmed competitor via `addCompetitors` with a short note on why they matter, plus `removeCompetitors` for entries you added that turned out irrelevant (leave rows the user added alone) — and append a research log entry: `{ appendResearchLog: { summary: "Competitive landscape: <market/query set>. Verdict: <conclusion>" } }`.

## OpenSEO MCP tools

- `research_keywords`: discover representative market queries.
- `get_keyword_metrics`: validate known query sets with volume, difficulty, intent, and trends.
- `get_serp_results`: identify recurring ranking domains across target queries.
- `find_serp_competitors`: compare domains competing across supplied keywords; use this before manual SERP counting when a keyword set is available.
- `get_domain_overview`: size organic footprint for candidate leaders.
- `get_search_console_performance`: when the user's own domain is in the comparison and Search Console is connected, anchor their position with first-party clicks/impressions/CTR rather than third-party estimates.
- `get_ranked_keywords`: find exact ranking keywords, URLs, ranks, intents, and SERP result types for leaders.
- `get_backlinks_overview`: compare backlink/referring-domain strength where relevant.
- `search_local_businesses`, `get_local_serp_results`, and `get_google_business_questions`: use for local SEO markets where proximity, Maps rankings, business categories, reviews, or Google Q&A affect who is winning.

## Workflow

1. Define the market query set:
   - Use provided keywords, or call `research_keywords` to build 5-10 representative queries.
   - Include mixed intent: informational, commercial, comparison, and tool/software terms when applicable.
   - For local SEO, include neighborhood/city/service-area queries and identify the priority locations or coordinates.
2. If the query set is already known, use `get_keyword_metrics` to validate relative demand and difficulty and `find_serp_competitors` to identify recurring domains at scale.
3. For local SEO, call `search_local_businesses` and `get_local_serp_results` for the highest-priority location(s) before synthesizing winners. Use `get_serp_results` as a complement for organic pages, not as the only local evidence.
4. Call `get_serp_results` for representative queries when live SERP composition, ranking URLs, or SERP features need inspection. Send at most 10 queries per call.
5. Identify recurring domains and group them by type:
   - Direct product competitors
   - Publishers/media
   - Marketplaces/directories
   - Communities/forums
   - Documentation/resources
6. For the strongest recurring domains, call `get_domain_overview`; default to the top 3-5 domains before expanding.
7. For direct competitors and relevant publishers, call `get_ranked_keywords`.
8. Use `get_backlinks_overview` when backlink authority appears important or the user asks why a domain is winning. Backlinks may be unavailable if the account has not enabled that data; continue with SERP/domain evidence if it fails.
9. Synthesize patterns: content types, themes, SERP formats, local-pack signals, authority advantages, and underserved angles.

## Output format

Start with the market read:

- Market leaders
- Most winnable opportunity area
- Biggest barrier to ranking

Then include:

| Domain | Type | Why they matter | Organic footprint | Winning themes | Weakness/gap |
| ------ | ---- | --------------- | ----------------- | -------------- | ------------ |

Add:

- Query set used
- Content formats that are working
- Keyword/theme gaps
- Backlink or authority observations
- Recommended next workflows: competitor analysis, keyword clustering, or content brief

## Guardrails

- Distinguish SEO competitors from business competitors.
- Do not overstate exact traffic when OpenSEO returns estimates.
- If using a small query set, call the result directional.
- Do not assume a publisher is a product competitor; label domain types clearly.
- For local markets, distinguish organic-page winners from Maps/local-pack winners.
competitive-landscape · 人気上昇中の Agent Skills | Mengbi