The Competitor Analysis Assistant is an advanced AI agent skill designed to break down competitor product positioning, feature variations, pricing strategies, and user reviews into structured, actionable market reports.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install qqyougit-competitor-analysis
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install qqyougit-competitor-analysis using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Competitor Analysis Assistant?
The Competitor Analysis Assistant is a structured intelligence tool built to deliver complete marketplace clarity. By leveraging Openclaw Skills, this agent meticulously dissects direct and indirect competition across multiple operational vectors. It eliminates guesswork by conducting factual market research, map-building, and objective user sentiment profiling to provide technical teams and product managers with highly specific roadmap strategies.
Rather than outputting generic pros and cons, the skill forces deep multi-dimensional alignment. It maps competitive realities against external industry pressures using standardized frameworks like Porter's Five Forces, PEST, and crossed SWOT matrix analysis. This ensures that any derived feature priorities or positioning tactics are grounded in verifiable public data points.
Competitor Analysis Assistant Use Cases
- New Product Launch Validation: Evaluate the viability of entering a market by identifying gaps left by existing direct or latent competitors.
- Feature Iteration & Prioritization: Map prospective product features against competitor matrices to isolate high-impact P0, P1, and P2 development choices.
- Pricing & Monetization Strategy Tuning: Breakdown tier structures (Free, Basic, Pro, Enterprise) of rivals to safely model hidden costs and optimal price elasticity.
- User Sentiment & Reputation Auditing: Analyze customer complaints and praise across multiple platforms to capitalize on competitor flaws.
- Strategic Benchmarking & Timeline Tracking: Establish rigorous baseline criteria to continually monitor long-term competitor movements and market share changes.
How Competitor Analysis Assistant Works
- Target Diagnosis: The agent defines the objective of the study (e.g., market entry, iteration) and determines the relevant industry segment (SaaS, E-commerce, App, Content, Hardware) to select appropriate frameworks like PEST or mapping profiles.
- Competitor Identification & Mapping: Organizes the competitive landscape strictly by tiering 3-5 direct competitors, 2-3 indirect competitors, and 1-2 latent or replacement options.
- Multi-Dimensional Comparison: Runs deep audits covering feature matrices, UX design choices, user acquisition loops, and monetization systems.
- Framework Synthesis: Generates concrete quantitative structures, detailing quantified Porter's Five Forces, a crossed SWOT strategy matrix, and interactive price vs. feature positioning maps.
- Opportunity Spotting: Isolates unfulfilled user pain points and market whitespace to establish defensible differentiators.
- Actionable Recommendations: Finalizes a rigorous roadmap mapping short-to-long term execution sequences coupled with key metrics for sustained tracking.
Competitor Analysis Assistant Setup
To deploy this competitor-analysis workflow into your local environment using Openclaw Skills, install the skill package directly using your system's agent package configuration:
openclaw skill install competitor-analysis
Ensure that proper web research integrations or search APIs are fully authorized in your agent profile configuration file to facilitate automated public data retrieval.
Competitor Analysis Assistant Data Schema & Taxonomy
The skill generates structured analytical content saved as markdown files, adhering to a strict data taxonomy. Output structures compile and separate data into distinct modules:
| Data Block | Type | Details |
|---|---|---|
| Overview | Metadata | Defines search scope, time thresholds, target industries, and analytical frameworks utilized. |
| Landscape Matrix | Data Table | Standardized breakdown mapping out positioning, pricing, market share estimates, and fundamental advantages. |
| Feature Grid | Checklist/Scores | Direct comparison matrix utilizing precise verification marks (Full Support, Partial Support, No Support) mapped alongside explicit resource sources. |
| Sentiment Tracker | List | Segmented aggregation of Top 3 positive and Top 3 negative user reviews pulled from at least 3 distinct channels, combined with Net Promoter Scores (NPS). |
| Strategic Matrix | Matrix Array | Actionable quad-cells detailing specific crossed strategies: SO (Strengths-Opportunities), ST (Strengths-Threats), WO (Weaknesses-Opportunities), and WT (Weaknesses-Threats). |
| Roadmap Plan | Timeline List | Actionable milestones categorized by priority tiers (P0, P1, P2) tied to expected outcomes. |
Competitor Analysis Assistant Advanced Features
- Data Validity Guardrails: Automatically enforces data cutoff dates and triggers hard web validation loops via search tools if stored profiles exceed 6 months old.
- Multi-Source Sentiment Verification: Mandates feedback acquisition across a minimum of 3 independent media channels (App Stores, social networks, industry papers) to filter bias.
- Strict Cross-SWOT Alignment: Disallows vague bulleted lists; forces at least 1 highly executable, actionable operational strategy per matrix cross-section.
- Granular Pricing Structural Breakdowns: Moves past simple pricing numbers to map hidden maintenance costs, feature-gate limitations, and freemium retention strategies.
SKILL.md
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