upgradeseo: Skill for Claude Code

.agents/skills/competitive-landscape/SKILL.md

competitive-landscape is a skill for Claude Code, Codex from upgrade-ventures/upgradeseo. It costs 22 tokens per session (883 once invoked), scanned A, a copy of competitive-landscape, MIT.

An SEO market-analysis workflow for studying which competitors lead search results, what topics they cover, which terms they rank for, and where gaps may exist.

In plain words
What is it for?
Researching market keywords, comparing competing domains, measuring their search visibility, examining content themes and backlinks, and identifying strategic gaps.
Why use it?
It gives a broader view of a market than examining one competitor at a time. It helps identify patterns and openings for new or better-targeted content.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: installed under .agents/ (shared by several agents).

This is upgrade-ventures/upgradeseo's own configuration. It tells Claude Code and Codex how to work on upgradeseo itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything upgradeseo configures →

Reuse

Borrowing it

Nothing to install: this file belongs to upgrade-ventures/upgradeseo. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/upgrade-ventures/upgradeseo/main/.agents/skills/competitive-landscape/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/upgrade-ventures/upgradeseo

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for competitive-landscape

README.md
[![agentmods](https://agentmods.dev/badge/skills/upgrade-ventures/upgradeseo/competitive-landscape.svg)](https://agentmods.dev/skills/upgrade-ventures/upgradeseo/competitive-landscape)
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<a href="https://agentmods.dev/skills/upgrade-ventures/upgradeseo/competitive-landscape"><img src="https://agentmods.dev/badge/skills/upgrade-ventures/upgradeseo/competitive-landscape.svg" alt="Measured on agentmods" height="20"></a>
Per session 22 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 883 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 95% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00022 $0.00883
Opus 5 $0.00011 $0.00441
Sonnet 5 $0.00004 $0.00177
Haiku 4.5 $0.00002 $0.00088

Measured 7d ago against content hash 71590b79342e, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

competitive-landscape scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

95% identical to competitive-landscape — 6 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

.agents/skills/competitive-landscape/SKILL.md · 81 lines

How it starts

The opening of the file, as written. The whole thing — 81 lines — stays where its author put it; the contents beside it link to each section on GitHub.

UpgradeSEO 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

UpgradeSEO 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.

Read the full file on GitHub · 81 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 7d ago First seen · 81 lines · 22 tokens per session scan A 71590b79342e

Subscribe to this mod's changes

competitive-landscape is a skill published in the GitHub repository upgrade-ventures/upgradeseo (1 stars, last pushed 21d ago), licensed MIT. It adds 22 tokens to every session and 883 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 95% identical to competitive-landscape, differing in 6 lines, and is treated as a copy.

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