Competitive Analysis
Analyze AI-search competitors for a query and recommend ranking strategy. Use when users ask competitor analysis, who ranks, or competitive landscape.
Install
$ agentstack add skill-mverab-egeoagents-competitive-analysis ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Links to your public security report.[](https://agentstack.voostack.com/security/report/skill-mverab-egeoagents-competitive-analysis) Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
Competitive Analysis Skill
When analyzing competition for AI-engine rankings:
Process
1. Identify the Query Space
- What queries would users search?
- What intent do these queries have?
- What type of content would AI engines prefer?
2. Generate Competitor Profiles
Create 5 realistic competitor archetypes:
| Type | Description | |------|-------------| | Market Leader | Established player with strong brand recognition | | Specialist | Niche focus with deep expertise | | Budget Option | Price-competitive alternative | | Innovator | New approach or technology | | Content King | Best educational/informational content |
3. Evaluate Ranking Factors
For each competitor, assess:
- Content depth and quality
- Social proof (reviews, testimonials, usage stats)
- Authority signals (expertise, credentials)
- User intent alignment
- Technical optimization (schema, structure)
4. Create Comparison Matrix
┌─────────────────────────────────────────────────────────────┐
│ 🏆 COMPETITIVE ANALYSIS │
├─────────────────────────────────────────────────────────────┤
│ │
│ Query: "[analyzed query]" │
│ │
│ RANKING PREDICTION │
│ ────────────────── │
│ #1 Market Leader ████████████ Strong brand + proof │
│ #2 Specialist ██████████ Deep expertise │
│ #3 YOUR CONTENT ████████ [current position] │
│ #4 Content King ██████ Good info, weak CTA │
│ #5 Budget Option ████ Price only │
│ │
│ YOUR DIFFERENTIATION OPPORTUNITY │
│ ───────────────────────────────── │
│ • [specific opportunity 1] │
│ • [specific opportunity 2] │
│ • [specific opportunity 3] │
│ │
└─────────────────────────────────────────────────────────────┘5. Recommend Strategy
Provide specific actions to outrank competitors:
- Content gaps to fill
- Social proof to add
- Unique angles to pursue
- Technical improvements
Output Requirements
- Always provide actionable differentiation strategies
- Be specific about what competitors do well/poorly
- Focus on what can realistically be improved
- Include estimated impact of changes
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: mverab
- Source: mverab/eGEOagents
- License: MIT
- Homepage: https://www.clawbiz.io/
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.