Analyze competitors and create competitive landscape documentation with feature matrices, positioning maps, and strategic recommendations. Use when asked to analyze competitors, create competitive analysis, compare features with competitors, build a competitive landscape, track competitive positioning, or prepare sales battlecard inputs. Produces structured competitor profiles, feature comparison matrix, win/loss analysis, and prioritised strategic recommendations. For a one-off teardown of a s…
Analyze competitors and create competitive landscape documentation with feature matrices, positioning maps, and strategic recommendations.
Use when asked to analyze competitors, create competitive analysis, compare features with competitors, build a competitive landscape, track competitive positioning, or prepare sales battlecard inputs.
Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.
Claude CodeNot declared
CursorNot declared
CodexNot declared
GitHub CopilotNot declared
WindsurfNot declared
Gemini CLINot declared
ClineNot declared
OpenCodeNot declared
Repository health
Stars1.3K
LicenseLICENSE
Default branchmain
Open issues7
Status
Active
Package contents
Files included with this skill beyond the listing page.
skill mdSKILL.md7,120 B
docsSUMMARY.md633 B
History
First seen on skills.sh
First recorded snapshot · 65 installs
SKILL.md
Competitive Analysis Skill
Create structured competitive analyses for product decision-making.
Reads from / Writes to the Brain
If a [professional-brain](../professional-brain/SKILL.md) (brain/) exists, ground in it instead of re-asking for what you already know:
Read first:knowledge/ (market + positioning) and competitor entities/. Run python3 ../professional-brain/scripts/brain_query.py ./brain "<competitor or market>" and carry each fact's provenance tag through — a competitor claim from a press release is [external], not [data].
📥 Propose to the Brain: after producing, propose recording new competitor facts to knowledge/ ([external]) and creating/updating competitor entities/. Show them, get a yes, then write with ../professional-brain/scripts/brain_write.py … --commit (append-only, dry-run by default).
Required Inputs
Ask the user for these if not provided:
Your product or company (what you're comparing against)
Competitors to analyze (or ask to identify the top 3-5)
Audience (product team / leadership / sales / board)
Process
Gather competitor information from provided inputs and available context
Build profiles for each competitor
Create feature comparison matrix on dimensions that matter to the user's customers
Analyze pricing and positioning
Identify win/loss patterns and strategic implications
Validate — Confirm all claims reference a specific source or are flagged as assumptions. Verify feature comparisons note quality differences, not just presence/absence.
Output Structure
1. Executive Summary
Market Position: Where we stand relative to competitors
Key Findings: Top 3-5 insights
Strategic Implications: What this means for the roadmap
2. Competitor Profiles
For each competitor:
Company Overview: Size, funding, market position
Target Customer: Who they serve
Value Proposition: Core positioning
Strengths / Weaknesses: What they do well and where they fall short
Recent Activity: Major updates, funding, announcements
3. Feature Comparison Matrix
Feature
Us
Competitor A
Competitor B
Competitor C
[Feature]
✅ Full
⚠️ Limited
❌ None
✅ Full
Legend: ✅ Full (production-ready) · ⚠️ Limited/Beta · ❌ None
Include notes on quality and implementation differences where significant.
4. Pricing Comparison
Plan
Us
Competitor A
Competitor B
Free/Trial
[price]
[price]
[price]
Pro
[price]
[price]
[price]
Enterprise
[price]
[price]
[price]
5. Market Positioning Map
Position competitors on two key dimensions relevant to the market:
Y-Axis: [e.g., Enterprise vs. SMB]
X-Axis: [e.g., Simple vs. Comprehensive]
Whitespace Opportunities: [Underserved segments]
6. Win/Loss Analysis
Why We Win:
Better at: [specific capabilities]
Customers who value: [what matters to them]
Why We Lose:
When customers need: [specific requirements]
Their advantage: [what tips the decision]
7. Strategic Recommendations
Immediate Actions (0-3 months):
[Action] — [Rationale]
Medium-term (3-12 months):
[Action] — [Rationale]
Anti-Patterns
Do not present competitor feature claims as facts without citing a source or flagging them as assumptions — outdated or incorrect feature data misleads sales and product decisions
Do not build a competitive analysis that only covers features — pricing, messaging, go-to-market motion, and who they hire for are equally strategic signals
Do not treat all buyers as identical — the same product may win against Competitor A in the enterprise segment and lose in SMB; segment-specific win/loss matters
Do not soften weaknesses and threats in the SWOT to avoid internal discomfort — an honest SWOT is only useful if the negatives are real
Deeper Materials
This skill ships with support files — use them when they are available:
references/feature-matrix-honesty.md — Feature Matrices That Don't Lie. Apply it while producing the output; it carries the calibration and judgment calls the method summary above compresses.
templates/landscape-doc.md — a fill-in version of the deliverable with the quality gates inline. Offer it when the user wants to work the document themselves rather than have it generated.
Scoring Rubric (0–40)
Score any output of this skill before handing it over; 32+ is ship-quality.
Dimension
0
5
10
Source hygiene
Competitor claims stated as fact with no provenance; stale data presented as current
Major claims sourced, but assumptions unflagged and mixed in with verified facts
Every claim carries a source tag or explicit assumption flag; an assumption register tells the reader what to re-verify
Depth beyond the feature checklist
A feature matrix and nothing else
Features plus pricing, but no positioning, GTM motion, or recent-moves analysis
Features, pricing, positioning map, and win/loss all present — with quality-difference notes where checkmark parity would mislead
Segment-aware win/loss
One generic strengths/weaknesses list averaged across all buyers
Win/loss present but undifferentiated by segment or based on internal opinion, not customer evidence
Win/loss split by segment with customer-voiced reasons and deal counts; contradicting segments (win SMB, lose enterprise) shown side by side