competitor-research
Skill53 starsChanged 5 days agoMITView on GitHub
Runs a 13-dimension dossier on a B2B SaaS competitor (product, ICP, pricing, reviews, content, launches, SEO/AEO, GTM, social, paid) with confidence levels, cited sources and a data-gaps list. Use when asked for competitor analysis, a competitive landscape or X vs Y.
29 other projects use a version of this.
Adopted by
Most recently taken up by
- TubeLabHQ/youtube-research-skillstheir own version, first seen Nov 15, 2026
- Synter-Media-AI/mcp-servertheir own version, first seen Nov 12, 2026
- openlegion-ai/openlegiontheir own version, first seen Nov 8, 2026
- kostja94/marketing-skillstheir own version, first seen Nov 8, 2026
- matteotitta/repo-structure-agencytheir own version, first seen Nov 8, 2026
- Ntmib/jarvis-architecttheir own version, first seen Nov 1, 2026
Used with
Projects with it also use level, messaging and 1 more.
Other files people use alongside this one.
Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
dachi-jp3Skilllevel
表示レベル(auto / low / medium / high)を切り替える。
Also in 3 projects that use this
VercelSkillmessaging
Use when turning settled positioning into the lines other people will reuse: the message hierarchy, value propositions per audience, objection handling, and the proof behind each claim.
Also in 4 projects that use this
ai-agents-for-agencies-coachesSkillbrand-kit
Establish and enforce per-client brand fidelity using the DESIGN.md standard (google-labs-code/design.md). Use whenever starting work for a client, creating any ad/landing-page/creative, or when brand colors/fonts/spacing are needed. Auto-extracts a client's visual identity into a validated DESIGN.md, keeps a central registry, and feeds the tokens into image-studio (statics), fb-ad-video-studio (video), and landing pages. Triggers: "set up brand for <client>", "make a DESIGN.md", "match the client's brand", "what are their brand colors", "new client onboarding", any creative work that must be on-brand.
Also in 4 projects that use this
Other versions29 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 29
- kostja94/marketing-skills★ 1.1ksame name
- explorium-ai/gtm-skills★ 346same name
- hamzafarooq/claude-code-starter★ 145same name
- marcosmodly/marketing-skill★ 141same name
- openlegion-ai/openlegion★ 130same name
- TubeLabHQ/youtube-research-skills★ 91same name
- smithjohn78390/smith--skills★ 41same name
- yangliu2060/smith--skills★ 40same name
- Synter-Media-AI/mcp-server★ 21same name
- jsath/claude-skills★ 14same name
19 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository9 other files it gives its agents.
- aeo-strategySkill
- battlecardsSkill
- case-studySkill
- company-contextSkill
- icp-researchSkill
- linkedin-profileSkill
- positioningSkill
- product-launchSkill
- tov-guidelinesSkill
The file
We split this skill into the rules it gives an agent
4 rules. 0 are common, 2 are distinctive, and 2 are very specific to this project.
0
Common
Most of the 21 edited versions we read keep these.
2
Distinctive
This author's own choices. Worth a look.
2
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 22
The Iron Law: no data point without source.
- Distinctive: line 37
If competitor name is ambiguous (e.g., "Cursor", "Base", "Linear"), confirm with the user before starting.
- Very specific: line 63
All 13 dimensions present (or marked [Not available] / [Requires premium tool] explicitly).
- Distinctive: line 89
Use when the standard 11-dimension company profile isn't enough — typically for direct-competitor showdowns or accounts where the champion …
“Common” is measured: kept by at least 6 in 10 of the 21 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Competitor research
Research substrate
When to run
Invoke when the user asks for: competitor analysis for X, battlecard research for X, competitive landscape for [market], compare X vs Y, what's [competitor] doing?. Do NOT invoke for: qualifying a company, product messaging only, researching the user's own company, or single-feature questions (answer directly).
Three run modes — pick by cadence and depth needed:
- First run (~90 min) —
/competitor-research [competitor]. New competitor, no existing dossier. Phases 1–3 (or 1–4 for aggregate). - Quick scan (~30 min, weekly) —
/competitor-research --quick [competitor]or/loop 1w. Refreshes fast-moving data only (news, Clay, G2, internal sources). Updates "Recent changes" header — sections without changes stay untouched. - Deep refresh (~90 min, monthly) —
/competitor-research --refresh [competitor]or/loop 1M. Full 13-dimension cycle with TrustPilot monitor and Phase 4 aggregate (if 2+ competitors refreshed this cycle).
Full cadence + refresh discipline → the premium reference. Visual phase map → the premium reference.
The Iron Law: no data point without source. Every claim cites a URL + access date or is marked [Not available]. Estimates need explicit confidence + reasoning. "Fast + wrong = useless."
Inputs
Required:
competitor name— exact company/product name (e.g.,Linear,Lovable).website URL— competitor's site (e.g.,linear.app).
Recommended (improve quality):
client context— current positioning sharpens the comparative angle.specific questions— focus areas (e.g., "deep dive on their pricing model and outbound motion").research mode—single deep dive(default) orcomparison matrix(3–6 competitors).
If competitor name is ambiguous (e.g., "Cursor", "Base", "Linear"), confirm with the user before starting. If website URL is missing, ask — don't guess.
Steps
- Confirm scope and disambiguate → the premium reference. Verify name + URL, select run mode, lock disambiguation.
- Pre-flight optional MCPs → check Clay, Granola, Google Drive, CRM, Notion availability per the premium reference ("Optional internal intel sources"). For each available, queue the corresponding queries; for each missing, skip silently.
- Research 13 dimensions → the premium reference. Order: Company → Product → ICP → Pricing → Reviews → Content → Launches → SEO/AEO → Technographics → Openings → GTM → LinkedIn/Social → Paid advertising. Each dimension has tool fallbacks (Ahrefs → Serper → manual; Apify → Firecrawl → manual). Frameworks + scoring → the premium reference ("Core frameworks").
- TrustPilot customer monitor (deep refresh only, customer-facing competitors only) → run inside Step 2.5 per the Phase 2 file. Score top 10–15 customers 🟢/🟡/🔴.
- Synthesize and assign confidence → the premium reference. Assign
[VERIFIED]/[INFERRED]/[ESTIMATED]/[UNAVAILABLE]per claim, write 2–3-paragraph executive summary, document data gaps with follow-up actions. - Aggregate analysis (only if 2+ competitors researched for same client) → the premium reference. Build threat matrix, feature parity table, credibility audit, 3–5 strategic recommendations. Save as
MMYY-aggregate-insights.mdin client's competitors folder. - Apply attribution standard — inline
(Source: X)per claim (not the verbose[VERIFIED: url, date]block); consolidate full URLs + access dates + confidence in the Sources & data quality table at the end of the document. Quality threshold: ≥50% Verified, ≤20% Estimated. - Write to client folder per output template → the premium reference ("Inline canonical, v2.7" — 13 dimensions, TrustPilot sub-section, Recent changes header, Sources & data quality table). For matrix mode → the premium reference ("Compact alternative"). Search query patterns per dimension → the premium reference. Common source URL patterns → the premium reference.
- Self-evaluate against quality gates → the premium reference. Run completeness, evidence-quality, and guardrail checks before declaring "done".
- Push to Notion (Competitor Research Database) and Google Docs (
client_folder/context/competitor-research/) per the push targets in frontmatter. For refresh mode, update the existing Notion page rather than creating a duplicate. - Offer iteration prompts post-delivery → the premium reference. If user signals approval (
"great research", quick approval), offer to save the output as a reference example under the premium reference.
What good looks like
Evaluations (binary pass/fail before declaring "done")
- ≥3 sources per major claim (revenue, funding, team size, pricing).
- ≥50%
[VERIFIED]confidence; ≤20%[ESTIMATED]. - Threat level set on every competitor:
PRIMARY/ENTERPRISE TIER/DIRECT ICP/STEALTH WATCH/LOW/DEFUNCT. - Inline
(Source: X)on every key data point (no verbose[VERIFIED: url, date]blocks inline). - Sources & data quality table at end-of-document with URLs + access dates + confidence per dimension.
- Data-gaps section non-empty if any dimension is incomplete or
[UNAVAILABLE]. - All 13 dimensions present (or marked
[Not available]/[Requires premium tool]explicitly). - Recent-changes header present in
--quickand--refreshmodes; "Last refreshed" date updated. - Output title is
# Competitor research: [Name]exactly — no aliases like "competitive intelligence analysis" or "Competitive Intelligence Report". - Premium-tool limitations noted explicitly (Ahrefs absent → Serper or manual, BuiltWith absent → "Not available", JS-walled ad libraries → manual check noted).
Scheduling (recurring runs)
/loop 1w /competitor-research --quick [competitor-name] # weekly quick scan, set-and-forget
/loop 1M /competitor-research --refresh [competitor-name] # monthly deep refresh, review-and-approve
/schedule create --name "competitor-[name]-weekly" --cron "0 9 * * 1" --prompt "/competitor-research --quick [name]"
/schedule create --name "competitor-[name]-monthly" --cron "0 9 1 * *" --prompt "/competitor-research --refresh [name]"For multiple competitors in parallel: /competitor-research --refresh --all spawns one subagent per competitor in the premium reference.
Sourced patterns — person-level competitor profiling
Standard /competitor-research profiles the company (11 dimensions covering positioning, pricing, features, content, GTM, team, funding, etc.). For deeper buyer-side intelligence, add a person-level layer that profiles the named decision-maker / champion / founder behind the competitor:
- Founder / CEO behavioral profile. Public-content cadence (LinkedIn, X, podcast appearances), preferred narratives, hiring-page tells (what roles they're scaling), customer-conversation patterns (testimonials they highlight, objections they pre-empt). Read for positioning intent — founders telegraph strategy in public.
- Champion persona at the buying account. Who actually drives the buy at their target accounts? Title patterns, tenure patterns, pain-point language (lifted from their case studies). This is the ICP-buyer side of the equation, not just the ICP-company side.
- Departure / hiring signals. Recent senior departures at the competitor = signal of internal tension; recent senior hires = signal of investment lane. Both inform competitive timing.
- Social-graph cluster. Who are they engaging with on LinkedIn? Who endorses them publicly? Builds a map of allied / adjacent companies that may be partnership or co-marketing candidates.
Use when the standard 11-dimension company profile isn't enough — typically for direct-competitor showdowns or accounts where the champion person is the deal-maker (mid-market and below).
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