A multi-tier data collector that identifies direct market competitors for any brand using real-time search results and intelligent AI fallback logic.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install competitor-finder
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 competitor-finder 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 Finder?
The Competitor Finder is a sophisticated research tool designed to populate the competitive landscape sections of marketing audits and strategic reports. By integrating this skill into your Openclaw Skills environment, you can automate the identification of 3-5 primary rivals for any brand name. It leverages a tiered priority system, starting with live search engine results and keyword-overlap data, ensuring high accuracy and up-to-date market insights.
This skill is built for resilience in production environments. It addresses the common challenge of API rate limits or missing data by employing a three-stage fallback strategy. Whether you are building a automated marketing agency or a brand tracking tool, this skill provides the structured data needed to understand market positioning without manual intervention.
Competitor Finder Use Cases
- Automating the Competitor Landscape section for professional Marketing Audit Pipelines.
- Building real-time market research agents within the Openclaw Skills ecosystem.
- Enriching CRM data with verified competitor URLs and business rationales.
- Benchmarking brand performance against live industry rivals during strategic planning.
How Competitor Finder Works
- Receives a brand name and optional domain through the input schema to provide context for the search.
- Executes a primary search via SerpAPI to find organic competitors and listicle-style rankings (e.g., "Top 10 Gymshark competitors").
- Triggers a secondary lookup via DataForSEO if the initial search is insufficient, utilizing domain-to-domain keyword overlap data.
- Initiates a minimal OpenAI GPT-4o-mini call as a last-resort fallback to ensure the skill always returns results even when search APIs are unavailable.
- Performs data normalization by stripping subdomains, deduplicating entries, and filtering out the original brand from the results.
- Returns a structured JSON payload containing the competitor name, website, and the specific reason they are considered a threat.
Competitor Finder Setup
To deploy this skill, configure the following environment variables in your project:
# Primary Search API
export SERPAPI_KEY="your_serp_api_key"
# Secondary SEO Data API
export DATAFORSEO_LOGIN="your_login"
export DATAFORSEO_PASSWORD="your_password"
# Last Resort Fallback
export OPENAI_API_KEY="your_openai_key"
Ensure you have the collector integrated into your pipeline logic to handle the returned CompetitorData interface.
Competitor Finder Data Schema & Taxonomy
The skill returns a structured object containing a list of competitor entries and optional error logging:
| Property | Type | Description |
|---|---|---|
competitors |
Array |
A collection of 3-5 identified competitor objects. |
competitors[].name |
string |
The verified name of the competitor brand. |
competitors[].website |
string |
The validated URL of the competitor. |
competitors[].reason |
string |
A brief explanation of the competitive relationship. |
error |
string |
(Optional) Included only if all collection methods fail to return data. |
Competitor Finder Advanced Features
- Three-tier fallback architecture (SerpAPI -> DataForSEO -> OpenAI) to maximize data availability for Openclaw Skills users.
- Automated result filtering that prevents the source brand from appearing in its own competitor list.
- Minimal token usage on fallback calls using GPT-4o-mini to keep operational costs extremely low.
- Graceful degradation through a custom error handling system that returns typed data instead of throwing exceptions.
- Winston logger integration for granular monitoring of API performance and fallback usage.
SKILL.md
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