Agent skill

Competitor Analysis

by OpenClaudia in OpenClaudia/openclaudia-skills

Conduct full competitor strategy breakdowns across SEO, ads, social, email, pricing, and positioning.

MITAuto-check passedMarketing & SEO

Install Competitor Analysis

skills CLI
$ npx skills add OpenClaudia/openclaudia-skills --skill competitor-analysis -a claude-code

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

GitHub CLI
$ gh skill install OpenClaudia/openclaudia-skills competitor-analysis --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/OpenClaudia/openclaudia-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/competitor-analysis .claude/skills/competitor-analysis && 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
competitor-analysis
GitHub stars
711
Token cost
~3.5k tokens
SKILL.md length
1,130 words
Files
1
Skills in repo
74
Repo updated
First seen
Licence
MIT

At a glance

Conduct full competitor strategy breakdowns across SEO, ads, social, email, pricing, and positioning.

  • Works in 10 steps: Gather Context → Competitor Identification → SEO Analysis → …
  • The user asks to analyze competitors
  • SKILL.md covers Optional API Integrations, Step 1: Gather Context, Step 2: Competitor… and Step 3: SEO Analysis, plus 7 more sections
  • Calls curl; reaches api.semrush.com and serpapi.com; needs SEMRUSH_API_KEY and SERPAPI_API_KEY

What it does

Competitor Analysis is an agent skill from OpenClaudia/openclaudia-skills. Conduct full competitor strategy breakdowns across SEO, ads, social, email, pricing, and positioning. Use when the user asks to analyze competitors, benchmark against rivals, understand competitive landscape, find competitor weaknesses, or build a competitive matrix. Trigger phrases include "competitor analysis", "competitive analysis", "who are my competitors", "competitor research", "competitive landscape", "benchmark competitors", "competitor ads", "competitor SEO", "competitor pricing", "SWOT analysis"…

Its SKILL.md is about 3.5k 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 Competitor analysis. It works with SerpApi and Google Ads. The repository describes itself as: 77 open-source marketing skills for Claude Code, Codex, and other AI coding agents. SEO, content, email, ads, analytics, and growth. The licence is MIT.

When your agent uses it

  • The user asks to analyze competitors
  • Benchmark against rivals
  • Understand competitive landscape
  • Find competitor weaknesses

Example prompts

  • “competitor analysis”
  • “competitive analysis”
  • “who are my competitors”
  • “/competitor-analysis”

Requirements

  • A credential in SEMRUSH_API_KEY
  • A credential in SERPAPI_API_KEY

Workflow steps

10 steps, taken from the step headings in SKILL.md.

  1. Gather Context
  2. Competitor Identification
  3. SEO Analysis
  4. Paid Advertising Analysis
  5. Social Media Analysis
  6. Email and Lifecycle Marketing
  7. Pricing and Positioning
  8. SWOT Analysis
  9. Competitive Matrix
  10. Strategic Recommendations

What it can do on your machine

Read from SKILL.md and the folder at commit 28bf209. 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

    Shell commands in SKILL.md call:

    • curl

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

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • api.semrush.com
    • serpapi.com
    • api.serpingapi.com

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

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • SEMRUSH_API_KEY
    • SERPAPI_API_KEY
    • SERPINGAPI_API_KEY
    • SCRAPINGBEE_API_KEY

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

Context cost

Competitor Analysis loads about 3.5k tokens when it runs. Until then it costs about 139 tokens; SKILL.md has 1,130 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~139
When it runs · the whole SKILL.md, loaded when a task matches
~3.5k

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 OpenClaudia/openclaudia-skills at commit 28bf209, republished under its MIT licence (© OpenClaudia). 1,130 words, ~3,479 tokens.

Download SKILL.mdSave it as .claude/skills/competitor-analysis/SKILL.md (or your agent's skills folder).
name
competitor-analysis
description
Conduct full competitor strategy breakdowns across SEO, ads, social, email, pricing, and positioning. Use when the user asks to analyze competitors, benchmark against rivals, understand competitive landscape, find competitor weaknesses, or build a competitive matrix. Trigger phrases include "competitor analysis", "competitive analysis", "who are my competitors", "competitor research", "competitive landscape", "benchmark competitors", "competitor ads", "competitor SEO", "competitor pricing", "SWOT analysis", "competitive matrix".

Competitor Analysis Framework

You are an expert competitive intelligence analyst. When the user asks you to analyze competitors, build competitive matrices, or identify competitive advantages, follow this framework.

Optional API Integrations

The following API keys enable richer data collection. All are optional -- the framework works without them using web search and manual research.

  • SEMRUSH_API_KEY - Domain overview, organic keywords, competitor discovery, traffic estimates
  • SERPAPI_API_KEY - Real-time SERP competitive analysis, ad copy extraction
  • SERPINGAPI_API_KEY - Real-time organic SERP positions and SERP features (free tier available)
  • SCRAPINGBEE_API_KEY - Scrape competitor pages that block direct fetching
SemRush API (if SEMRUSH_API_KEY available)

Domain Overview - Get traffic, keywords, and authority for any competitor:

bash
# Domain overview (organic traffic, keywords, authority score)
curl -s "https://api.semrush.com/?type=domain_ranks&key=${SEMRUSH_API_KEY}&export_columns=Db,Dn,Rk,Or,Ot,Oc,Ad,At,Ac&domain={competitor_domain}"

Columns: Db=Database, Dn=Domain, Rk=Rank, Or=Organic Keywords, Ot=Organic Traffic, Oc=Organic Cost, Ad=Adwords Keywords, At=Adwords Traffic, Ac=Adwords Cost.

Organic Keywords - See what keywords a competitor ranks for:

bash
# Top organic keywords for a competitor domain
curl -s "https://api.semrush.com/?type=domain_organic&key=${SEMRUSH_API_KEY}&domain={competitor_domain}&database=us&export_columns=Ph,Po,Nq,Cp,Ur,Tr&display_limit=50&display_sort=tr_desc"

Columns: Ph=Keyword, Po=Position, Nq=Search Volume, Cp=CPC, Ur=URL, Tr=Traffic %.

Competitor Discovery - Find domains competing for the same keywords:

bash
# Domains competing with a given domain in organic search
curl -s "https://api.semrush.com/?type=domain_organic_organic&key=${SEMRUSH_API_KEY}&domain={domain}&database=us&export_columns=Dn,Cr,Np,Or,Ot,Oc&display_limit=20"

Columns: Dn=Domain, Cr=Competition Level, Np=Common Keywords, Or=Organic Keywords, Ot=Organic Traffic, Oc=Organic Cost.

Keyword Gap - Find keywords competitors rank for but you do not:

bash
curl -s "https://api.semrush.com/?type=domain_domains&key=${SEMRUSH_API_KEY}&domains=*|or|{your_domain}|*|or|{competitor1}|*|or|{competitor2}&database=us&export_columns=Ph,P0,P1,P2,Nq,Cp&display_limit=50&display_filter=%2B|P0|Eq|0"

The filter +|P0|Eq|0 returns keywords where your domain (position 0) does not rank.

SerpAPI (if SERPAPI_API_KEY available)

SERP Competitive Analysis - See who ranks for key terms in real time:

bash
# Real-time SERP for competitive keywords
curl -s "https://serpapi.com/search.json?q={keyword}&api_key=${SERPAPI_API_KEY}&num=20&gl=us&hl=en"

Use this to:

  • Identify which competitors dominate organic results for target keywords (parse organic_results)
  • Extract competitor ad copy from ads and shopping_results fields
  • Discover related competitor keywords from related_searches
  • See competitor presence in SERP features: knowledge_graph, local_results, featured_snippet

Google Ads Competitor Analysis:

bash
# Search a commercial keyword to see competitor ads
curl -s "https://serpapi.com/search.json?q={commercial_keyword}&api_key=${SERPAPI_API_KEY}&gl=us&hl=en"

The response ads array contains: position, title, link, displayed_link, tracking_link, description, sitelinks. This reveals competitor ad copy, landing pages, and messaging.

Serping API (if SERPINGAPI_API_KEY available)

SERP Competitive Analysis - Same use as SerpAPI above, for organic results and SERP features (web search only — no ads or shopping_results). Also usable when no SerpAPI key is configured:

bash
# Real-time SERP for competitive keywords
curl -s -X POST "https://api.serpingapi.com/v1/search" \
  -H "X-API-Key: ${SERPINGAPI_API_KEY}" \
  -H "Content-Type: application/json" \
  -d '{"q": "{keyword}", "gl": "us", "hl": "en", "num": 20}'

Use this to:

  • Identify which competitors dominate organic results for target keywords (parse organic: position, title, link, snippet)
  • Discover related competitor keywords from relatedSearches (.query)
  • See competitor presence in SERP features: knowledgeGraph, answerBox, peopleAlsoAsk
  • Add "tbs": "qdr:m" to see who ranked in the last month, or "location" for a local SERP

Errors are {"error": {"code", "message"}}; on 429 quota_exceeded tell the user the monthly quota is spent and fall back to WebSearch.

ScrapingBee (if SCRAPINGBEE_API_KEY available)

Use ScrapingBee to scrape competitor pages that block direct fetching via WebFetch (e.g., JavaScript-heavy pages, bot-protected sites, pricing pages):

bash
# Scrape a competitor page
curl -s "https://app.scrapingbee.com/api/v1/?api_key=${SCRAPINGBEE_API_KEY}&url={url}&render_js=false"

Set render_js=true if the page requires JavaScript rendering (SPAs, dynamic pricing tables). Useful for:

  • Extracting pricing page details when WebFetch returns incomplete content
  • Scraping competitor landing pages for messaging and positioning analysis
  • Capturing competitor feature comparison pages
  • Getting content from sites that block automated requests

Note: ScrapingBee charges per request. Use sparingly -- try WebFetch first and fall back to ScrapingBee only when needed.

Step 1: Gather Context

Establish: user's product, industry/vertical, target audience, known competitors, key concerns (pricing, features, marketing), available tools (SEMrush, Ahrefs, SimilarWeb), goal (strategy, launch decision, investor deck, repositioning).

Step 2: Competitor Identification

Three Categories
  • Direct (same product, same audience): 3-5 competitors
  • Indirect (different product, same problem): 2-3 competitors
  • Aspirational (market leaders to learn from): 1-2 competitors
Discovery Methods

Google "[category]" (ads + organic top 10), G2/Capterra "Compare" pages, Reddit/Twitter "[competitor] alternative", customer interviews, job postings, funding announcements, SEMrush "Competing Domains" report.

Step 3: SEO Analysis

If SEMRUSH_API_KEY is available, use the Domain Overview and Organic Keywords endpoints (see Optional API Integrations above) to populate the profile below with real data. If SERPAPI_API_KEY or SERPINGAPI_API_KEY is available, supplement with real-time SERP position data. Otherwise, use WebSearch and public tools to estimate.

For each competitor:

COMPETITOR SEO PROFILE: [Company Name]
DA/DR: [score] | Monthly Organic Traffic: [volume] | Ranking Keywords: [total]

TOP KEYWORDS: [keyword, position, volume, traffic share]

CONTENT STRATEGY:
  Post frequency, avg length, content types, top 5 performing URLs

BACKLINK PROFILE:
  Total backlinks, referring domains, top linking domains, acquisition rate

TECHNICAL: Site speed, mobile optimization, schema markup, architecture
Show full SKILL.md (544 more words)Show less
Traffic Source Reality Check (do this BEFORE trusting the numbers)

A headline like "74% organic" does not mean a competitor is winning at SEO discovery. Most tools report the last click, which hides where awareness was actually created. Decompose before you draw conclusions:

  1. Branded vs non-branded search. Tag every keyword containing the brand name (normalize out spaces/dots so auto ppt matches autoppt). Branded search = people who already know the name navigating back, not Google discovering them.
  2. Navigational bucket = branded search + Direct traffic. Treat them as one: an existing audience returning, not new acquisition.
  3. Genuinely acquisitive search = non-branded organic (generic terms, competitor-brand terms, how-to content). This is the only slice that is truly SEO-driven discovery — size it explicitly.
  4. Reconcile your tools. A big SimilarWeb/whole-funnel total vs a small Ahrefs/SemRush organic estimate means heavy untracked long-tail (often non-English). Different top-countries between tools = discovery happens where users are, not where rankings are tracked.
  5. Sanity-check the users are real. Bounce rate, pages/visit, time-on-site. Bot/incentivized traffic shows as ~100% bounce, 1 page, a few seconds.

Channel fingerprint → find the real top-of-funnel. Key diagnostic: when branded search + direct dominate but no last-click acquisition channel is large, the discovery engine is upstream and invisible to these tools.

FingerprintReal growth engine
High branded search + high direct, but social/referral/paid all smallOff-last-click: short-video (TikTok/Reels/Shorts), messaging apps, word-of-mouth — strips referrers, resurfaces later as brand search + direct
High non-branded organic, deep blog/long-tailGenuine SEO content engine (editorial or programmatic)
Ranks on competitors' brand names (<rival> alternative, <rival> pricing)Deliberate competitor-interception SEO
High referrals concentrated in few domainsPartnerships / directories / affiliate / integrations
High paid + displayPaid acquisition (check if profitable for the niche)
genAI referral channel non-trivial and growingLLM-citation traffic (ChatGPT/Perplexity)

Confirm, don't assert: search the brand on YouTube/TikTok for a viral wave; check whether branded-search growth lagged a social spike; name the actual top referrers; read who the content is written for; let top countries tell you the community. Only then write the "how they really grow" verdict.

Gap Analysis
  • Keyword gaps: Keywords competitors rank for that you do not
  • Content gaps: Topics competitors cover that you do not
  • Backlink gaps: Domains linking to competitors but not you

Step 4: Paid Advertising Analysis

COMPETITOR AD PROFILE: [Company Name]
Est. Monthly Spend: [range] | Platforms: [list] | Active Ads: [count]

GOOGLE ADS: Top keywords, ad copy themes, landing pages, extensions
META ADS: Ad count (from Ad Library), formats, running duration, creative themes
LINKEDIN ADS (B2B): Formats, targeting signals, content themes

Key questions: Which keywords bid most aggressively? What landing pages do ads point to (reveals best offers)? How long have top ads been running (long = profitable)? Running retargeting?

Step 5: Social Media Analysis

| Platform | Followers | Frequency | Avg Engagement | Top Content Type |
|----------|-----------|-----------|----------------|-----------------|
| Twitter/X | ... | ... | ... | ... |
| LinkedIn | ... | ... | ... | ... |
| Instagram | ... | ... | ... | ... |
| YouTube | ... | ... | ... | ... |

CONTENT THEMES: [theme, engagement level] x3
TOP POSTS (last 90 days): [platform, description, metrics]
COMMUNITY: Response time, tone, UGC, community spaces

Step 6: Email and Lifecycle Marketing

Sign up for every competitor's list, trial, and newsletter. Track:

  • Newsletter: Frequency, content type, subject line style, personalization
  • Onboarding sequence: Day-by-day breakdown with subject, purpose, CTA
  • Promotions: Discount frequency, seasonal campaigns, urgency tactics
  • Retention: Churn prevention emails, re-engagement campaigns

Step 7: Pricing and Positioning

Pricing Comparison
| Feature/Plan | You | Comp A | Comp B | Comp C |
|-------------|-----|--------|--------|--------|
| Free Tier | ... | ... | ... | ... |
| Starter | ... | ... | ... | ... |
| Pro | ... | ... | ... | ... |
| Enterprise | ... | ... | ... | ... |

Note model type, billing options, add-ons, discounts, price anchoring.

Positioning Map

Create a 2x2 map on the two most important dimensions (e.g., Price vs. Simplicity). Identify white space opportunities.

Messaging Extraction

For each: tagline, value proposition, key differentiator, target persona, tone, primary proof points.

Step 8: SWOT Analysis

For each major competitor:

STRENGTHS: [with evidence]
WEAKNESSES: [with evidence from reviews, complaints, feature gaps]
OPPORTUNITIES: [market trends in their favor]
THREATS: [your advantages or market shifts against them]

Weakness sources: G2/Capterra 1-2 star reviews, Reddit/Twitter complaints, Glassdoor, Down Detector, feature comparison gaps, support forums.

Step 9: Competitive Matrix

| Dimension | You | Comp A | Comp B | Comp C |
|-----------|-----|--------|--------|--------|
| Founded | ... | ... | ... | ... |
| Funding/Revenue | ... | ... | ... | ... |
| Target Market | ... | ... | ... | ... |
| Entry Price | ... | ... | ... | ... |
| Key Differentiator | ... | ... | ... | ... |
| DA | ... | ... | ... | ... |
| Monthly Traffic | ... | ... | ... | ... |
| G2 Rating | ... | ... | ... | ... |
| Feature 1-3 | Y/N | Y/N | Y/N | Y/N |

Step 10: Strategic Recommendations

STRATEGIC RECOMMENDATIONS
==========================
1. POSITIONING: Current vs. recommended position, key message, differentiation
2. CONTENT: Priority keywords, content types, topics to own
3. PAID: Keywords competitors miss, ad angles, channel priorities
4. PRODUCT: Features to build (from gaps), features to deprioritize
5. PRICING: Adjustments, packaging opportunities
6. QUICK WINS: 3 actions to implement this week

Ground every recommendation in specific competitor data. Prioritize by impact and ease of implementation.

© OpenClaudia, 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 skills/competitor-analysis of OpenClaudia/openclaudia-skills.

Open the folder on GitHubat commit 28bf209

Compare with similar skills

Competitor Analysis 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.

Competitor Analysis compared with similar skills
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SEO Content Brief GeneratorAgriciDaniel/claude-seo18k2 repos~2.6kAutomated safety check: PassMIT
Blog GoogleAgriciDaniel/claude-blog2.3k1 repos~3.3kAutomated safety check: NotesMIT
Startup Competitorsferdinandobons/startup-skill1.2k1 repos~4.1kAutomated safety check: PassMIT
Amazon Listing Competitor Analysisbrowser-act/skills6.1k2 repos~3.2kAutomated safety check: PassMIT

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Categories

Questions about Competitor Analysis

What does Competitor Analysis do?

Conduct full competitor strategy breakdowns across SEO, ads, social, email, pricing, and positioning. Competitor Analysis is an agent skill from OpenClaudia/openclaudia-skills. Conduct full competitor strategy breakdowns across SEO, ads, social, email, pricing, and positioning.

When should I use Competitor Analysis?

Competitor Analysis fits situations like: the user asks to analyze competitors; benchmark against rivals; understand competitive landscape; find competitor weaknesses.

How do I install Competitor Analysis in Claude Code?

Run `npx skills add OpenClaudia/openclaudia-skills --skill competitor-analysis -a claude-code`. Or copy the skill folder (skills/competitor-analysis in OpenClaudia/openclaudia-skills) into .claude/skills/competitor-analysis in your project. Claude Code loads it when a task matches its description.

How do I install Competitor Analysis in Codex?

Run `npx skills add OpenClaudia/openclaudia-skills --skill competitor-analysis -a codex`. Or copy the skill folder (skills/competitor-analysis in OpenClaudia/openclaudia-skills) into .agents/skills/competitor-analysis in your project. Codex loads it when a task matches its description.

Can I use Competitor Analysis 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 OpenClaudia/openclaudia-skills --skill competitor-analysis -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/competitor-analysis, .gemini/skills/competitor-analysis, .github/skills/competitor-analysis and .opencode/skills/competitor-analysis in your project.

What does Competitor Analysis need to run?

Going by SKILL.md and its folder, Competitor Analysis needs the command-line tools its instructions call (curl) and credentials named SEMRUSH_API_KEY, SERPAPI_API_KEY, SERPINGAPI_API_KEY and SCRAPINGBEE_API_KEY. Our summary lists: A credential in SEMRUSH_API_KEY; A credential in SERPAPI_API_KEY.

Does Competitor Analysis access the network?

SKILL.md names 3 domains. In commands or code: api.semrush.com, serpapi.com and api.serpingapi.com; the agent is likely to contact these when it follows the instructions. This is read from the text; nothing was executed.

Is Competitor Analysis 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 Competitor Analysis use?

Competitor Analysis 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 Competitor Analysis use?

About 3.5k tokens (SKILL.md is roughly 14k 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 Competitor Analysis?

Skills that share tags, products or a category with Competitor Analysis: Competitor Ads Analyst (thatrebeccarae/claude-marketing, 162 stars), SEO Content Brief Generator (AgriciDaniel/claude-seo, 18k stars), Blog Google (AgriciDaniel/claude-blog, 2.3k stars) and Startup Competitors (ferdinandobons/startup-skill, 1.2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Competitor Analysis?

OpenClaudia (a GitHub organization) maintains it in OpenClaudia/openclaudia-skills, which has 711 GitHub stars. The repository holds 74 skills in this directory. The repository was last updated on September 18, 2026.

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