A lightweight attribution model designed to connect content outputs directly to business outcomes and ROI.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install creator-attribution-lite
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 creator-attribution-lite 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 Creator Attribution Lite?
Creator Attribution Lite is a specialized measurement tool for creators and small teams who need to move beyond vanity metrics. It bridges the gap between content production and practical business results by identifying which specific posts drive leads, sales, and high-value conversions. As part of the Openclaw Skills ecosystem, it provides a transparent way to prioritize high-ROI content types without the complexity of a full business intelligence suite.
By focusing on engagement quality, click intent, and conversion signals, this skill allows users to make data-backed decisions. Whether you are reviewing small-team performance or refining a content strategy, it offers directional evidence to ensure every piece of content serves a strategic purpose.
Creator Attribution Lite Use Cases
- Identifying which social media posts or articles drove the most clicks and sales.
- Prioritizing content types that yield the highest return on investment.
- Making quick performance decisions for small teams without complex BI tools.
- Running simulations to predict potential content impact when real data is scarce.
- Feeding winning content patterns back into creative templates for future production.
How Creator Attribution Lite Works
- Data Validation: The skill checks for minimum required fields including content ID, date, platform, views, clicks, and downstream metrics like signups or GMV.
- Funnel Mapping: Every content item is classified into a specific stage: awareness, consideration, or conversion.
- Impact Scoring: A transparent, weighted formula calculates an impact score based on engagement quality, click intent, and conversion signals.
- Decision Output: The system generates a ranked list of performers, a list of items to pause or optimize, and three recommended content bets with specific rationales.
Creator Attribution Lite Setup
To integrate this measurement capability into your workflow, ensure your environment supports Openclaw Skills and install the package via your terminal:
# Install the skill into your project directory
openclaw install creator-attribution-lite
# Configure your data source (CSV or JSON)
openclaw config set attribution_source=./data/content_metrics.json
Once installed, you can trigger an analysis by providing a content list with associated campaign metadata.
Creator Attribution Lite Data Schema & Taxonomy
The skill expects a structured dataset to perform accurate attribution. Below is the required schema for content items:
| Field | Description | Requirement |
|---|---|---|
content_id |
Unique identifier for the post or asset | Mandatory |
platform |
The channel where content was published | Mandatory |
views_watch |
Top-of-funnel reach metrics | Mandatory |
clicks |
Mid-funnel engagement signal | Mandatory |
conversions |
Downstream business outcomes (sales/leads) | Mandatory |
funnel_stage |
Awareness, Consideration, or Conversion | Optional (Auto-mapped) |
All outputs include a confidence note based on sample size and data quality to ensure auditable results.
Creator Attribution Lite Advanced Features
- Simulation Mode: Generate synthetic performance data to test strategy outcomes when real-world data is missing.
- Creatop Handoff: Automatically export winning patterns and high-performing structures back to creative templates.
- Explainable AI Formula: Access the specific weighting logic used for normalization to audit the attribution methodology.
- Directional Evidence Engine: Focuses on actionable trends rather than overclaiming causality on small datasets.
SKILL.md
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