MoizIbnYousaf/marketing-cli

openseo-competitive-landscape

Map who is winning an SEO market with measured data — recurring SERP domains, organic footprints, winning content themes, backlink authority, and the gaps worth attacking. Use this skill for market-level questions ("who ranks for X", "how competitive is this space", "where are the SEO openings") before committing to keyword targets or content themes. For one named competitor, use openseo-competitor-analysis instead. Triggers: "competitive landscape seo", "who ranks for", "seo market map", "how c

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See how to use itView GitHub source
npx skills add https://github.com/MoizIbnYousaf/marketing-cli --skill "skills/openseo-competitive-landscape"
Automated source guide

Source checked Jul 28, 2026·Refresh due Oct 26, 2026

Reorganized from the pinned upstream SKILL.md

Turn openseo-competitive-landscape's source instructions into a guide you can follow

According to the pinned SKILL.md from MoizIbnYousaf/marketing-cli: Answer with measured data: who is winning this SEO market, what content works for them, and where the openings are. Findings update brand/landscape.md (mktg's market memory) with an evidence tier mktg's landscape-scan cannot reach alone.

npx skills add https://github.com/MoizIbnYousaf/marketing-cli --skill "skills/openseo-competitive-landscape"
Check the pinned source

Best fit

  • Map who is winning an SEO market with measured data — recurring SERP domains, organic footprints, winning content themes, backlink authority, and the gaps worth attacking. Use this skill for market-level questions ("who ranks for X", "how competitive is this space", "where are the SEO openings") before committing to keyword targets or content themes. For one named competitor, use openseo-competitor-analysis instead. Triggers: "competitive landscape seo", "who ranks for", "seo market map", "how c

Bring this context

  • A concrete task that matches the documented purpose of openseo-competitive-landscape.
  • The files, examples, or context the task depends on.
  • Your constraints, target environment, and definition of done.

Expected outputs

  • A result that follows the pinned openseo-competitive-landscape instructions.
  • A concise record of assumptions, inputs used, and unresolved questions.
  • A final check against the source workflow and relevant permission signals.

Key source sections

Read openseo-competitive-landscape through these 5 source sections

Sections are extracted automatically from the pinned SKILL.md and link back to the source.

01

Workflow

1. Define the market query set (positioning-filtered, mixed intent). 2. findserpcompetitors for recurring domains; getkeywordmetrics to validate demand/difficulty. 3. Group recurring domains by type: direct product competitors, publishers/media, marketplaces/directories, communi…

SKILL.md · Workflow
Define the market query set (positioning-filtered, mixed intent).findserpcompetitors for recurring domains; getkeywordmetrics to validate demand/difficulty.Group recurring domains by type: direct product competitors, publishers/media, marketplaces/directories, communities/forums, docs/resources.
02

On Activation

1. Catalog + binding: mktg catalog info openseo --json --fields configured + .seo/openseo.json. No OpenSEO → fall back to landscape-scan (Exa qualitative) and label authority/metrics unknown. 2. Brand grounding: read brand/landscape.md + brand/competitors.md (tolerate templates)…

SKILL.md · On Activation
Catalog + binding: mktg catalog info openseo --json --fields configured + .seo/openseo.json. No OpenSEO → fall back to landscape-scan (Exa qualitative) and label authority/metrics unknown.Brand grounding: read brand/landscape.md + brand/competitors.md (tolerate templates) — known competitors seed the query set; positioning filters "SEO competitor" from "business competitor."1. Catalog + binding: mktg catalog info openseo --json --fields configured + .seo/openseo.json. No OpenSEO → fall back to landscape-scan (Exa qualitative) and label authority/metrics unknown. 2. Brand grounding: read br…
03

OpenSEO MCP Tools

researchkeywords + getkeywordmetrics: build + validate a 5–10 query market set (mixed intent: informational, commercial, comparison, tool terms).

SKILL.md · OpenSEO MCP Tools
researchkeywords + getkeywordmetrics: build + validate a 5–10 query market set (mixed intent: informational, commercial, comparison, tool terms).findserpcompetitors: recurring domains across the keyword set at scale — use before manual SERP counting.getserpresults: inspect live SERP composition/features (≤10 queries per call).
04

Output Format

Review the “Output Format” section in the pinned source before continuing.

SKILL.md · Output Format
Review and apply the “Output Format” source section.
05

Anti-Patterns

Adapted from every-app/open-seo .agents/skills/competitive-landscape (MIT). Workflow upstream; mktg brand-memory writes and fallback wiring added here.

SKILL.md · Anti-Patterns
Treating business competitors as SEO competitors — because the company that competes for customers often isn't who competes for SERPs (publishers and directories win informational queries). Label domain types; never mer…Quoting estimate numbers as exact traffic — because third-party organic estimates can be off by multiples, and a plan built on fake precision breaks on contact with reality. Say "estimate" or "directional."Small query sets presented as market truth — because 4 queries is a peek, not a map. Call small-set results directional and say what would confirm them.

SkillSignal prompt templates

Provide the task, context, and acceptance criteria

These prompts were written by SkillSignal from the source structure; they are not upstream text.

Task-start prompt

Confirm source fit, inputs, and outputs before acting.

Use openseo-competitive-landscape to help me with: [specific task]. Context: [files, data, or background]. Constraints: [environment, scope, and prohibited actions]. Before acting, check the pinned SKILL.md and explain which sections apply, what inputs are still missing, and what you will deliver.

Source-guided execution

Make the Agent explicitly follow the key extracted sections.

Apply the pinned openseo-competitive-landscape source to [task]. Pay particular attention to these source sections: “Workflow”, “On Activation”, “OpenSEO MCP Tools”, “Output Format”, “Anti-Patterns”. Preserve the important decision at each step. Mark facts not covered by the source as “needs confirmation” instead of inventing them. Then verify the result against my acceptance criteria: [criteria].

Result-review prompt

Check omissions, permissions, and source drift before delivery.

Review the current openseo-competitive-landscape result: (1) does it satisfy the original task; (2) were any applicable steps or limits in the pinned SKILL.md missed; (3) did it perform any unauthorized file, command, network, or data action; and (4) which conclusions remain unverified? List issues first, then fix only what the source or user authorization supports.

Output checklist

Verify each item before delivery

The task matches the purpose documented in the SKILL.md.

The source section “Workflow” has been checked.

The source section “On Activation” has been checked.

The source section “OpenSEO MCP Tools” has been checked.

The source section “Output Format” has been checked.

Inputs, constraints, and acceptance criteria are explicit.

Unverified facts, compatibility, and outcome claims are clearly marked.

Any file, command, network, or data action has been reviewed.

Choose a different workflow

When another Skill is the better fit

competitor-alternatives

Creates high-converting 'X vs Y' and 'X alternatives' SEO pages that capture comparison search traffic. Researches competitors, writes honest comparison content, and adds schema markup (FAQPage, ItemList). Use when someone needs alternatives pages, comparison content, or says 'alternatives page', 'vs page', 'comparison', 'competitor alternatives', 'X vs Y page', or wants to capture competitor brand search traffic with SEO content. Also trigger when someone wants to rank for competitor brand name

A separate implementation from MoizIbnYousaf/marketing-cli; compare its source, maintenance signals, and permission requirements.

Open source detail

seo-content

Create high-quality, SEO-optimized content that ranks AND reads like a human wrote it. Performs live SERP gap analysis, writes with anti-AI detection techniques, and adds schema markup. Use when someone needs a blog post, article, SEO page, or wants content that drives search traffic. Triggers on 'SEO content', 'blog post', 'article', 'SERP', 'programmatic SEO', 'content at scale', 'write a post about', 'rank for', or 'search-optimized content'. Two modes: single article or programmatic SEO at s

A separate implementation from MoizIbnYousaf/marketing-cli; compare its source, maintenance signals, and permission requirements.

Open source detail

openseo-competitor-analysis

Deep-dive ONE competitor's organic footprint — exact ranking keywords and URLs, content themes, backlink profile, and exploitable gaps — with findings written into brand/competitors.md. Use this skill when the user names a competitor and wants to know what to learn from them, counter, or outrank, including head-to-head comparisons against the user's own domain. For market-level mapping first, use openseo-competitive-landscape. Triggers: "analyze competitor", "competitor keywords", "competitor ba

A separate implementation from MoizIbnYousaf/marketing-cli; compare its source, maintenance signals, and permission requirements.

Open source detail

FAQ

What does openseo-competitive-landscape do?

Answer with measured data: who is winning this SEO market, what content works for them, and where the openings are. Findings update brand/landscape.md (mktg's market memory) with an evidence tier mktg's landscape-scan cannot reach alone.

How do I start using openseo-competitive-landscape?

The catalog detected this source-specific install command: npx skills add https://github.com/MoizIbnYousaf/marketing-cli --skill "skills/openseo-competitive-landscape". Inspect the command and pinned source before running it.

Which Agent platforms does it declare?

No dedicated Agent platform is declared in the pinned source record.

Repository stars
27
Repository forks
5
Quality
75/100
Source repository last pushed

Quality breakdown

Based on traceable docs and repository signals; stars are not treated as quality.

75/100
Documentation22/30
Specificity18/25
Maintenance20/20
Trust signals15/25

Compare before choosing

Related Agent Skills and source variants

These links are selected from shared tasks, functions, stacks, platforms, and same-name variants. Compare the source owner, documentation, permissions, and maintenance signals.

competitor-alternatives by MoizIbnYousaf

Creates high-converting 'X vs Y' and 'X alternatives' SEO pages that capture comparison search traffic. Researches competitors, writes honest comparison content, and adds schema markup (FAQPage, ItemList). Use when someone needs alternatives pages, comparison content, or says 'alternatives page', 'vs page', 'comparison', 'competitor alternatives', 'X vs Y page', or wants to capture competitor brand search traffic with SEO content. Also trigger when someone wants to rank for competitor brand name

seo-content by MoizIbnYousaf

Create high-quality, SEO-optimized content that ranks AND reads like a human wrote it. Performs live SERP gap analysis, writes with anti-AI detection techniques, and adds schema markup. Use when someone needs a blog post, article, SEO page, or wants content that drives search traffic. Triggers on 'SEO content', 'blog post', 'article', 'SERP', 'programmatic SEO', 'content at scale', 'write a post about', 'rank for', or 'search-optimized content'. Two modes: single article or programmatic SEO at s

openseo-competitor-analysis by MoizIbnYousaf

Deep-dive ONE competitor's organic footprint — exact ranking keywords and URLs, content themes, backlink profile, and exploitable gaps — with findings written into brand/competitors.md. Use this skill when the user names a competitor and wants to know what to learn from them, counter, or outrank, including head-to-head comparisons against the user's own domain. For market-level mapping first, use openseo-competitive-landscape. Triggers: "analyze competitor", "competitor keywords", "competitor ba

openseo-keyword-research by MoizIbnYousaf

Discover keyword opportunities with MEASURED volume, keyword difficulty, CPC, and intent from OpenSEO, then write them into brand/keyword-plan.md. Use this skill whenever someone asks for keyword difficulty, KD, search volume, keyword ideas with metrics, striking-distance opportunities from Search Console, or SERP-validated keyword priorities. For qualitative research without an OpenSEO connection, use mktg's keyword-research instead (metrics will be unknown). Triggers: "keyword difficulty", "se

openseo-coach by MoizIbnYousaf

Friendly SEO coach mode for the mktg + OpenSEO stack. Use this skill when the user is new to SEO, unsure which SEO workflow to run, asks "what does OpenSEO do", wants strategy explained in plain language, or needs help choosing between keyword research, clustering, competitive analysis, and link prospecting. Triggers: "seo coach", "new to seo", "explain openseo", "what seo should i do", "seo strategy help".

View original Skill.mdThis page is parsed directly from the repository SKILL.md without editorial rewriting. Collected: Jul 28, 2026 · about 3 min

OpenSEO Competitive Landscape

Answer with measured data: who is winning this SEO market, what content works for them, and where the openings are. Findings update brand/landscape.md (mktg's market memory) with an evidence tier mktg's landscape-scan cannot reach alone.

On Activation

  1. Catalog + binding: mktg catalog info openseo --json --fields configured + .seo/openseo.json. No OpenSEO → fall back to landscape-scan (Exa qualitative) and label authority/metrics unknown.
  2. Brand grounding: read brand/landscape.md + brand/competitors.md (tolerate templates) — known competitors seed the query set; positioning filters "SEO competitor" from "business competitor."

OpenSEO MCP Tools

  • research_keywords + get_keyword_metrics: build + validate a 5–10 query market set (mixed intent: informational, commercial, comparison, tool terms).
  • find_serp_competitors: recurring domains across the keyword set at scale — use before manual SERP counting.
  • get_serp_results: inspect live SERP composition/features (≤10 queries per call).
  • get_domain_overview: organic footprint for top 3–5 recurring domains.
  • get_ranked_keywords: exact ranking keywords/URLs/intents for leaders.
  • get_backlinks_overview: authority comparison where rankings look authority-driven (may be unavailable on some accounts — continue without it).
  • get_search_console_performance: when the user's own domain is compared and GSC is connected, anchor THEIR side with first-party data instead of third-party estimates.

Workflow

  1. Define the market query set (positioning-filtered, mixed intent).
  2. find_serp_competitors for recurring domains; get_keyword_metrics to validate demand/difficulty.
  3. Group recurring domains by type: direct product competitors, publishers/media, marketplaces/directories, communities/forums, docs/resources.
  4. get_domain_overview top 3–5; get_ranked_keywords for direct competitors + relevant publishers; get_backlinks_overview where authority explains wins.
  5. Synthesize: winning content types, SERP formats, authority advantages, underserved angles.
  6. Update brand/landscape.md: leaders, winnable area, biggest barrier, query set used, content formats that work, keyword/theme gaps — dated, with the measured-vs-estimate caveat.
  7. Recommend next: openseo-competitor-analysis (one domain), openseo-keyword-clustering (page mapping), or seo-content.

Output Format

DomainTypeWhy they matterOrganic footprintWinning themesWeakness/gap

Anti-Patterns

  • Treating business competitors as SEO competitors — because the company that competes for customers often isn't who competes for SERPs (publishers and directories win informational queries). Label domain types; never merge the lists.
  • Quoting estimate numbers as exact traffic — because third-party organic estimates can be off by multiples, and a plan built on fake precision breaks on contact with reality. Say "estimate" or "directional."
  • Small query sets presented as market truth — because 4 queries is a peek, not a map. Call small-set results directional and say what would confirm them.
  • Stopping at "X is winning" without the why — because a leader list with no content-theme or authority explanation gives the user nothing to act on. Every leader gets a "why they win" and a "where they're weak."
  • Abandoning the analysis when backlinks are unavailable — because SERP + domain evidence still answers "who and what." Degrade gracefully and name the missing tier.

Adapted from every-app/open-seo .agents/skills/competitive-landscape (MIT). Workflow upstream; mktg brand-memory writes and fallback wiring added here.

Skill path
skills/openseo-competitive-landscape/SKILL.md
Commit SHA
f12fbcbe4929
Repository license
MIT
Data collected