Competitor Finder

Identify your competitive set and map their positioning, messaging, pricing, and channel activity. Uses Perplexity for competitive intelligence. Output is the foundation that competitor-analyzer and competitor-visual enrich.

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Purpose

Competitor Finder is the starting point of competitive intelligence. It answers:

• Who are we actually competing with? (direct AND indirect)
• How does each competitor position themselves?
• What are their core value propositions and target audiences?
• What pricing models and ranges do they use?
• Which marketing channels are they active on?
• Where are the gaps and opportunities?

The output — research-memory/competitive-intel.md — is the skeleton that two downstream skills build upon:

• competitor-analyzer (Firecrawl) adds website messaging detail: headlines, CTAs, pricing pages, social proof
• competitor-visual (Playwright) adds design audit: screenshots, color palettes, layout patterns, visual tone

"You can't differentiate if you don't know what you're differentiating FROM." — The Boring Marketer

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Modes

Mode	When to Use	Behavior
Full Discovery	No competitive-intel.md exists, or it's an empty scaffold	Run all 5 steps from scratch
Refresh	competitive-intel.md already has [competitor-finder] data	Check research-log.md for last scan date → add new competitors or update existing profiles

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Auto-Load Protocol

On every invocation, BEFORE any research:

1. Check research-memory/ directory
2. If files exist → Read ALL .md files (except README.md)
3. Priority context from market-landscape.md:
   • Market category definition → sets competitor search scope
   • Market structure (price tiers, channels) → provides classification frame
   • Market size → helps gauge competitive intensity
4. Check brand-memory/ (read-only) → If exists, use business description, positioning, and target audience as self-reference context
5. If competitive-intel.md has [competitor-finder] data AND research-log.md shows a previous scan → suggest Refresh mode

Enrichment preservation rule: When loading existing competitive-intel.md, NEVER delete or overwrite sections tagged [competitor-analyzer] or [competitor-visual]. Only touch [competitor-finder] sections.

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Input Gathering

Collect from the user conversationally. Do NOT dump a form — ask naturally.

Field	Required	Description
Business / Product description	YES	What does the company/product do?
Known competitors	Optional	Starting points for competitive mapping
Business model	Optional	SaaS, service, e-commerce, education, etc. — frames pricing comparison
Geography / Market scope	Optional	Global or specific region — bounds competitor search
Focus area	Optional	Pricing comparison, messaging differentiation, channel strategy, etc.
Research intensity	Optional	"light" / "standard" / "deep" (default: deep) — 리서치 깊이와 수집량 조절
Language	Optional	결과물 작성 언어 (default: English)

If brand-memory/ exists, pre-fill business description, positioning, and target audience from voice-profile.md and positioning.md — ask user to confirm or correct.

If market-landscape.md exists, show the market category and structure as context: "Based on your market scan, I'll search for competitors in [category]. Does this look right?"

If this is a Refresh, show the current competitive set and ask: "Any new competitors to add? Or specific profiles to update?"

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Research Intensity

사용자가 명시적으로 요청하면 리서치 깊이를 조절합니다. 지정하지 않으면 deep (기본값).

Level	search_context_size	수집량	용도
light	low	축소 (~50%)	빠른 감 잡기
standard	medium	보통 (~75%)	일반 리서치
deep	high	전체 (100%)	본격 리서치

"가볍게", "빠르게", "간단히" → light / "보통으로", "적당히" → standard / 별도 지정 없음 → deep

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Process

Step 1: Load Context & Set Search Scope

Goal: Establish the competitive search frame using existing research.

Actions:

• Load all research-memory/ files
• Extract from market-landscape.md (if available):
  • Market category → primary search term
  • Price tiers → competitor classification frame
  • Channels → where to look for competitors
  • Adjacent markets → source of indirect competitors
• Extract from brand-memory/ (if available):
  • Own positioning → identify who occupies similar territory
  • Target audience → find who targets the same people
• If competitive-intel.md exists with data → switch to Refresh mode

Output: Clear search scope definition (category + constraints).

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Step 2: Identify Competitive Set (Direct + Indirect)

Goal: Build a comprehensive list of direct and indirect competitors with URLs.

Tool: perplexity_reason (classification reasoning required)

Query pattern:

Who are the main competitors for a [business description] in the [market category] space?

Identify:
1. Direct competitors (5-8): Same target audience, similar solution, same category
2. Indirect competitors (2-3): Different approach to same problem, OR adjacent category players expanding into this space

For EACH competitor, provide:
- Company name
- Website URL (homepage)
- One-line description of what they do
- Classification: direct or indirect, with reasoning

Parameters:

• search_context_size: Research Intensity에 따라 결정 (light→"low" / standard→"medium" / deep→"high")

경쟁사 수집 목표: light=3-5 direct + 1-2 indirect / standard=4-6 direct + 2 indirect / deep=5-8 direct + 2-3 indirect

If user provided known competitors: Include them in the query as starting points and ask Perplexity to validate + expand: "I already know about [names]. Who else competes in this space?"

Output: Competitive set table — names, URLs, descriptions, classifications.

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Step 3: Build Competitor Profiles (Positioning, Messaging, Pricing)

Goal: Map each competitor's basic positioning, value proposition, audience, and pricing.

Tool: perplexity_ask (factual data collection)

Query pattern:

For each of these competitors in the [market category]:
[list competitor names from Step 2]

Analyze each one:
1. Positioning: How do they describe themselves? (tagline, hero headline, or elevator pitch)
2. Core value propositions: Top 2-3 benefits they emphasize
3. Target audience: Who are they built for? (job titles, company sizes, demographics)
4. Pricing model: Free / Freemium / Subscription / One-time / Enterprise
5. Price range: Approximate price points or tiers

Cite their website or recent coverage as source for each data point.

Parameters:

• search_context_size: Research Intensity에 따라 결정 (light→"low" / standard→"medium" / deep→"high")

light일 경우 상위 경쟁사 위주로 프로필을 작성합니다 (전체 대상이 아닌 핵심 경쟁사 중심).

If competitors are numerous (8+): Split into two queries to avoid shallow coverage.

Output: Positioning & Messaging Matrix for all competitors.

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Step 4: Channel Activity + Gap Analysis

Goal: Map competitors' marketing channel presence and identify whitespace opportunities.

Tool: perplexity_ask

Query pattern:

What marketing channels are these [market category] competitors most active on?
[list competitor names]

For each competitor, assess presence and activity level on:
- Content marketing (blog, YouTube, podcast)
- Social media (which platforms, approximate follower counts or engagement level)
- SEO / Paid advertising
- Email / Newsletter
- Community / Events

Rate each: Strong / Moderate / Weak / Absent

Then identify:
1. Underserved channels: Which channels do MOST competitors neglect?
2. Positioning whitespace: What positioning angles are unclaimed?
3. Messaging gaps: What customer needs are competitors NOT addressing in their messaging?

Parameters:

• search_recency_filter: "month"
• search_context_size: Research Intensity에 따라 결정 (light→"low" / standard→"medium" / deep→"high")

Output: Channel Activity Matrix + Gaps & Opportunities section.

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Step 5: Save & Log

Goal: Write all findings to research-memory/competitive-intel.md and log execution.

5a. Write competitive-intel.md

Language rule: 섹션 헤더와 테이블 컬럼명은 영어로 유지합니다. 본문, 셀 값, 설명, 분석 텍스트는 사용자가 지정한 언어로 작성합니다. 언어가 지정되지 않으면 English로 작성합니다.

Use the exact schema in references/competitive-intel-schema.md. Key rules:

• Tag every section you write with [competitor-finder]
• Leave [competitor-analyzer] and [competitor-visual] sections as empty scaffolds with HTML comments
• For Refresh: update only [competitor-finder] sections; NEVER touch other skills' sections

5b. Update research-log.md

Append one row:

| [YYYY-MM-DD] | competitor-finder | Full Discovery / Refresh | [X direct + Y indirect identified, key gaps] | Perplexity |

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Perplexity MCP Tool Guide

Tool	When to Use	This Skill
perplexity_reason	Classification, reasoning	Step 2: Competitive set identification + direct/indirect classification
perplexity_ask	Factual Q&A, current data	Step 3: Competitor profiles, Step 4: Channel activity
perplexity_search	Find specific URLs/sources	Only if competitor website URLs need verification

Common parameters:

• search_context_size: Research Intensity 레벨에 따라 결정 — 위 Research Intensity 테이블 참조
• search_recency_filter: "month" for Step 4 (latest channel activity), default for Steps 2-3

Query best practices:

• Include market category in every query (from market-landscape.md or user input)
• Always request website URLs — competitor-analyzer and competitor-visual depend on them
• Ask for source citations for positioning claims
• One topic per query: Don't combine competitor identification + profiling in one call
• For 8+ competitors, split profiling into two queries to ensure depth
• Language: 사용자가 English 외 언어를 지정한 경우, 모든 query 끝에 "Respond in [language]."를 추가

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Quality Checklist

Before saving, verify:

• Direct 경쟁사 최소 3개 (light) ~ 8개 (deep) 식별 (with URLs)
• Indirect 경쟁사 최소 1개 (light) ~ 3개 (deep) 식별 (with URLs)
• Every competitor has: positioning, value props, target audience, pricing
• Channel Activity Matrix covers at least 4 of 5 channel types
• Gaps & Opportunities section has at least one finding per sub-section
• All sections tagged with [competitor-finder]
• Downstream sections ([competitor-analyzer], [competitor-visual]) are empty scaffolds
• All Perplexity responses include source citations
• research-log.md updated with execution record
• Competitor URLs are valid homepage links (not 404s or redirects)

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Example (Abbreviated)

Input: "Marketing education business selling AI-powered skill packs to solo marketers and small teams."

Direct Competitors (5):

1. Marketing Examined (Alex Garcia) — Newsletter-based marketing education
2. CopyBlogger — Content marketing & copywriting education platform
3. DigitalMarketer — Comprehensive digital marketing training + certifications
4. Demand Curve — Growth marketing education (YC-backed)
5. MarketingProfs — B2B marketing education + events

Indirect Competitors (2):

1. ChatGPT / Claude — AI directly performing marketing tasks (substitutes education)
2. Canva — Design tool with built-in marketing education content

Key Gaps:

• No competitor offers "AI + marketing" skill packs as a combined product
• Newsletter-based education is crowded; actionable skill/template bundles are rare
• Most competitors weak on community-driven learning

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What This Skill Does NOT Do

• Website scraping / messaging detail → Use competitor-analyzer (Firecrawl)
• Screenshots / design patterns → Use competitor-visual (Playwright)
• Customer profiling → Use audience-profiler
• Customer language mining → Use voice-of-customer
• Strategic recommendations → Use research-synthesizer (reads this output)

Competitor Finder stays focused on who the competitors are and how they position at a high level — the foundation for deeper competitive analysis.