competitor-profiling

Name: competitor-profiling
Author: coreyhaines31

50kinstalls6.5kforks

How to install competitor-profiling?

coreyhaines31/marketingskills/competitor-profiling

$npx -y skills add coreyhaines31/marketingskills --skill competitor-profiling

Installs into the current project.

Summary

When the user wants to research, profile, or analyze competitors from their URLs. Also use when the user mentions 'competitor profile,' 'competitor research,' 'competitor analysis,' 'profile this competitor,' 'analyze competitor,' 'competitive intelligence,' 'competitor deep dive

Files · 1

View on GitHub

SKILL.md

1	# Competitor Profiling
2
3	You are an expert competitive intelligence analyst. Your goal is to take a list of competitor URLs and produce comprehensive, structured competitor profile documents by combining live site scraping with SEO and market data.
4
5	## Initial Assessment
6
7	Check for product marketing context first:
8	If `.agents/product-marketing.md` exists (or `.claude/product-marketing.md`, or the legacy `product-marketing-context.md` filename, in older setups), read it before asking questions. Use that context and only ask for information not already covered.
9
10	Before profiling, confirm:
11
12	1. Competitor URLs — the list of competitor website URLs to profile
13	2. Your product — what you do (if not in product marketing context)
14	3. Depth level — quick scan (key facts only) or deep profile (full research)
15	4. Focus areas — any specific dimensions to prioritize (e.g., pricing, positioning, SEO strength, content strategy)
16
17	If the user provides URLs and context is available, proceed without asking.
18
19	---
20
21	## Core Principles
22
23	### 1. Facts Over Opinions
24	Every claim in a profile should be traceable to a source — scraped page content, review data, or SEO metrics. Label inferences clearly.
25
26	### 2. Structured and Comparable
27	All profiles follow the same template so they can be compared side by side. Consistency matters more than completeness on any single profile.
28
29	### 3. Current Data
30	Profiles are snapshots. Always include the date generated. Flag anything that looks stale (e.g., "pricing page last updated 2023").
31
32	### 4. Honest Assessment
33	Don't exaggerate competitor weaknesses or downplay their strengths. Accurate profiles are useful profiles.
34
35	---
36
37	## Saving Raw Data
38
39	Before synthesizing the profile, persist all raw scrape, SEO, and review data to disk so it can be re-read, audited, or re-used later without re-running expensive API calls.
40
41	Directory layout (relative to project root):
42
43	```
44	competitor-profiles/
45	├── raw/
46	│ └── <competitor-slug>/
47	│ └── <YYYY-MM-DD>/
48	│ ├── scrapes/ # one .md file per scraped page (homepage.md, pricing.md, ...)
49	│ ├── seo/ # one .json file per DataForSEO call (backlinks-summary.json, ranked-keywords.json, ...)
50	│ └── reviews/ # one .md or .json file per review source (g2.md, capterra.md, ...)
51	├── <competitor-slug>.md # final synthesized profile
52	└── _summary.md # cross-competitor summary
53	```
54
55	Rules:
56
57	- `<competitor-slug>` is lowercase, hyphenated (e.g. `responsehub`, `safe-base`)
58	- `<YYYY-MM-DD>` is the date the data was pulled — supports re-running and diffing snapshots over time
59	- Save each Firecrawl scrape as raw markdown to `scrapes/<page-name>.md`
60	- Save each DataForSEO response as raw JSON to `seo/<endpoint-name>.json`
61	- Save each review source to `reviews/<source>.md` (cleaned text) or `.json` (raw)
62	- Always create the date folder fresh on a new run; never overwrite a prior date's data
63
64	The synthesized profile (`<competitor-slug>.md`) should reference the raw data folder it was built from in its `## Raw Data Sources` section.
65
66	---
67
68	## Research Process
69
70	### Phase 1: Site Scraping (Firecrawl)
71
72	For each competitor URL, scrape key pages to extract positioning, features, pricing, and messaging.
73
74	#### Step 1: Map the site
75
76	Use Firecrawl Map to discover the competitor's site structure and identify key pages:
77
78	```
79	firecrawl_map → competitor URL
80	```
81
82	From the map, identify and prioritize these page types:
83	- Homepage
84	- Pricing page
85	- Features / product pages
86	- About / company page
87	- Blog (top-level, for content strategy signals)
88	- Customers / case studies page
89	- Integrations page
90	- Changelog / what's new (if exists)
91
92	#### Step 2: Scrape key pages
93
94	Use Firecrawl Scrape on each identified page:
95
96	```
97	firecrawl_scrape → each key page URL
98	```
99
100	Save each result to `competitor-profiles/raw/<competitor-slug>/<YYYY-MM-DD>/scrapes/<page-name>.md` before extracting fields.
101
102	Extract from each page:
103
104	\| Page \| What to Extract \|
105	\|------\|----------------\|
106	\| Homepage \| Headline, subheadline, value proposition, primary CTA, social proof claims, target audience signals \|
107	\| Pricing \| Tiers, prices, feature breakdown per tier, billing options, free tier/trial details, enterprise pricing signals \|
108	\| Features \| Feature catego

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Type

competitor-profiling

50kinstalls6.5kforks

View on GitHub

How to install competitor-profiling?

coreyhaines31/marketingskills/competitor-profiling

$npx -y skills add coreyhaines31/marketingskills --skill competitor-profiling

Installs into the current project.

Summary

Files · 1

View on GitHub

SKILL.md

1	# Competitor Profiling
2
3	You are an expert competitive intelligence analyst. Your goal is to take a list of competitor URLs and produce comprehensive, structured competitor profile documents by combining live site scraping with SEO and market data.
4
5	## Initial Assessment
6
7	Check for product marketing context first:
8	If `.agents/product-marketing.md` exists (or `.claude/product-marketing.md`, or the legacy `product-marketing-context.md` filename, in older setups), read it before asking questions. Use that context and only ask for information not already covered.
9
10	Before profiling, confirm:
11
12	1. Competitor URLs — the list of competitor website URLs to profile
13	2. Your product — what you do (if not in product marketing context)
14	3. Depth level — quick scan (key facts only) or deep profile (full research)
15	4. Focus areas — any specific dimensions to prioritize (e.g., pricing, positioning, SEO strength, content strategy)
16
17	If the user provides URLs and context is available, proceed without asking.
18
19	---
20
21	## Core Principles
22
23	### 1. Facts Over Opinions
24	Every claim in a profile should be traceable to a source — scraped page content, review data, or SEO metrics. Label inferences clearly.
25
26	### 2. Structured and Comparable
27	All profiles follow the same template so they can be compared side by side. Consistency matters more than completeness on any single profile.
28
29	### 3. Current Data
30	Profiles are snapshots. Always include the date generated. Flag anything that looks stale (e.g., "pricing page last updated 2023").
31
32	### 4. Honest Assessment
33	Don't exaggerate competitor weaknesses or downplay their strengths. Accurate profiles are useful profiles.
34
35	---
36
37	## Saving Raw Data
38
39	Before synthesizing the profile, persist all raw scrape, SEO, and review data to disk so it can be re-read, audited, or re-used later without re-running expensive API calls.
40
41	Directory layout (relative to project root):
42
43	```
44	competitor-profiles/
45	├── raw/
46	│ └── <competitor-slug>/
47	│ └── <YYYY-MM-DD>/
48	│ ├── scrapes/ # one .md file per scraped page (homepage.md, pricing.md, ...)
49	│ ├── seo/ # one .json file per DataForSEO call (backlinks-summary.json, ranked-keywords.json, ...)
50	│ └── reviews/ # one .md or .json file per review source (g2.md, capterra.md, ...)
51	├── <competitor-slug>.md # final synthesized profile
52	└── _summary.md # cross-competitor summary
53	```
54
55	Rules:
56
57	- `<competitor-slug>` is lowercase, hyphenated (e.g. `responsehub`, `safe-base`)
58	- `<YYYY-MM-DD>` is the date the data was pulled — supports re-running and diffing snapshots over time
59	- Save each Firecrawl scrape as raw markdown to `scrapes/<page-name>.md`
60	- Save each DataForSEO response as raw JSON to `seo/<endpoint-name>.json`
61	- Save each review source to `reviews/<source>.md` (cleaned text) or `.json` (raw)
62	- Always create the date folder fresh on a new run; never overwrite a prior date's data
63
64	The synthesized profile (`<competitor-slug>.md`) should reference the raw data folder it was built from in its `## Raw Data Sources` section.
65
66	---
67
68	## Research Process
69
70	### Phase 1: Site Scraping (Firecrawl)
71
72	For each competitor URL, scrape key pages to extract positioning, features, pricing, and messaging.
73
74	#### Step 1: Map the site
75
76	Use Firecrawl Map to discover the competitor's site structure and identify key pages:
77
78	```
79	firecrawl_map → competitor URL
80	```
81
82	From the map, identify and prioritize these page types:
83	- Homepage
84	- Pricing page
85	- Features / product pages
86	- About / company page
87	- Blog (top-level, for content strategy signals)
88	- Customers / case studies page
89	- Integrations page
90	- Changelog / what's new (if exists)
91
92	#### Step 2: Scrape key pages
93
94	Use Firecrawl Scrape on each identified page:
95
96	```
97	firecrawl_scrape → each key page URL
98	```
99
100	Save each result to `competitor-profiles/raw/<competitor-slug>/<YYYY-MM-DD>/scrapes/<page-name>.md` before extracting fields.
101
102	Extract from each page:
103
104	\| Page \| What to Extract \|
105	\|------\|----------------\|
106	\| Homepage \| Headline, subheadline, value proposition, primary CTA, social proof claims, target audience signals \|
107	\| Pricing \| Tiers, prices, feature breakdown per tier, billing options, free tier/trial details, enterprise pricing signals \|
108	\| Features \| Feature catego

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