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Agent skill

Competitive Landscape

by petera2c in petera2c/simple-table

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

MITAuto-check passedMarketing & SEO

Install Competitive Landscape

skills CLI
$ npx skills add petera2c/simple-table --skill competitive-landscape -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install petera2c/simple-table competitive-landscape --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/petera2c/simple-table.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/competitive-landscape .claude/skills/competitive-landscape && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
competitive-landscape
GitHub stars
229
Used in
3 other repos
Token cost
~1.1k tokens
SKILL.md length
492 words
Files
1
Skills in repo
9
Repo updated
First seen
Licence
MIT

At a glance

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

  • Works in 9 steps: Define the market query set → If the query set is already known, use… → For local SEO, call… → …
  • Tasks that involve Link building
  • SKILL.md covers Goal, Required inputs, OpenSEO MCP tools and Workflow, plus 2 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Competitive Landscape is an agent skill from petera2c/simple-table. Map SEO market leaders, winning content themes, keyword coverage, backlinks, and strategic gaps.

Its SKILL.md is about 1.1k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Marketing & SEO, covering Link building. The repository describes itself as: Lightweight data grid/table for fast, modern web apps. The licence is MIT.

When your agent uses it

  • Tasks that involve Link building

Example prompts

  • “/competitive-landscape”

Workflow steps

9 steps, taken from the first numbered list in SKILL.md.

  1. Define the market query set
  2. If the query set is already known, use get_keyword_metrics to validate relative demand and difficulty and find_serp_competitors to…
  3. For local SEO, call search_local_businesses and get_local_serp_results for the highest-priority location(s) before synthesizing winners…
  4. Call get_serp_results for representative queries when live SERP composition, ranking URLs, or SERP features need inspection. Send at most…
  5. Identify recurring domains and group them by type
  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…
  9. Synthesize patterns: content types, themes, SERP formats, local-pack signals, authority advantages, and underserved angles.

What it can do on your machine

Read from SKILL.md and the folder at commit df2dda2. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Competitive Landscape loads about 1.1k tokens when it runs. Until then it costs about 30 tokens; SKILL.md has 492 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~30
When it runs · the whole SKILL.md, loaded when a task matches
~1.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from petera2c/simple-table at commit df2dda2, republished under its MIT licence (© petera2c). 492 words, ~1,067 tokens.

Download SKILL.mdSave it as .claude/skills/competitive-landscape/SKILL.md (or your agent's skills folder).
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

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.
Show full SKILL.md (102 more words)Show less

Output format

Start with the market read:

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

Then include:

DomainTypeWhy they matterOrganic footprintWinning themesWeakness/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.

© petera2c, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in .agents/skills/competitive-landscape of petera2c/simple-table.

Open the folder on GitHubat commit df2dda2

Used in 3 other repositories

We found 4 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 3 other GitHub owners. This page covers the copy in petera2c/simple-table, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Competitive Landscape next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Competitive Landscape compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Competitive Landscape this skillpetera2c/simple-table2293 repos~1.1kAutomated safety check: PassMIT
FLOW SEO FrameworkAgriciDaniel/claude-seo18k2 repos~1.4kAutomated safety check: PassMIT
SEO DataforseoAgriciDaniel/codex-seo7912 repos~4.6kAutomated safety check: PassMIT
Backlink CheckRyze-AI-Adgent/open-seo-mcp-skills4.5k—~515Automated safety check: PassMIT
Beyondseobeyondtahir/beyondseo157—~4.3kAutomated safety check: PassMIT
Webobsidianxnohat/webobsidian268—~2.1kAutomated safety check: PassMIT

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Categories

Questions about Competitive Landscape

What does Competitive Landscape do?

Map SEO market leaders, winning content themes, keyword coverage, backlinks, and strategic gaps. Competitive Landscape is an agent skill from petera2c/simple-table. Map SEO market leaders, winning content themes, keyword coverage, backlinks, and strategic gaps.

When should I use Competitive Landscape?

Competitive Landscape fits situations like: tasks that involve Link building.

How do I install Competitive Landscape in Claude Code?

Run `npx skills add petera2c/simple-table --skill competitive-landscape -a claude-code`. Or copy the skill folder (.agents/skills/competitive-landscape in petera2c/simple-table) into .claude/skills/competitive-landscape in your project. Claude Code loads it when a task matches its description.

How do I install Competitive Landscape in Codex?

Run `npx skills add petera2c/simple-table --skill competitive-landscape -a codex`. Or copy the skill folder (.agents/skills/competitive-landscape in petera2c/simple-table) into .agents/skills/competitive-landscape in your project. Codex loads it when a task matches its description.

Can I use Competitive Landscape in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add petera2c/simple-table --skill competitive-landscape -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/competitive-landscape, .gemini/skills/competitive-landscape, .github/skills/competitive-landscape and .opencode/skills/competitive-landscape in your project.

What does Competitive Landscape need to run?

SKILL.md names no scripts, command-line tools or credentials: Competitive Landscape is instructions for the agent only.

Does Competitive Landscape access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Competitive Landscape safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Competitive Landscape use?

Competitive Landscape is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Competitive Landscape use?

About 1.1k tokens (SKILL.md is roughly 4.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Competitive Landscape?

Skills that share tags, products or a category with Competitive Landscape: FLOW SEO Framework (AgriciDaniel/claude-seo, 18k stars), SEO Dataforseo (AgriciDaniel/codex-seo, 791 stars), Backlink Check (Ryze-AI-Adgent/open-seo-mcp-skills, 4.5k stars) and Beyondseo (beyondtahir/beyondseo, 157 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Competitive Landscape?

petera2c (a GitHub user) maintains it in petera2c/simple-table, which has 229 GitHub stars. The repository holds 9 skills in this directory. The repository was last updated on October 4, 2026.

Source: petera2c/simple-table on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.