A systematic research tool for analyzing super-individuals, creator brands, and one-person businesses using structured public data.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install cell-opc-case-research
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 cell-opc-case-research 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 OPC Case Research?
OPC Case Research is a specialized skill for the Openclaw Skills ecosystem designed to conduct deep-dive investigations into super-individuals and creator-led IPs. It focuses on transforming scattered public information into actionable business intelligence, specifically targeting content strategy, monetization models, and channel growth. By enforcing a strict separation between facts, inferences, and unknowns, this skill ensures that developers and researchers get a high-integrity view of how one-person businesses actually operate.
This skill is particularly valuable for users who need to move beyond surface-level observations. It provides a rigorous framework for mapping source evidence, constructing event timelines, and evaluating the replicability of successful business paths. Whether you are performing a fast initial screen or a deep-dive technical report, it ensures your findings are grounded in verifiable public data.
OPC Case Research Use Cases
- Identifying the core monetization strategies of successful niche creators.
- Mapping the evolution and platform shifts of a super-individual through a detailed timeline.
- Benchmarking content strategy and IP positioning against industry leaders.
- Screening creator cases to determine suitability for deeper strategic study.
- Generating structured research reports for creator-economy analysis.
How OPC Case Research Works
- Define the research target and depth level (quick, standard, or deep) to establish the scope within the Openclaw Skills framework.
- Map primary and secondary sources, prioritizing first-party statements and official landing pages over third-party summaries.
- Construct a chronological event sequence of 5 to 20 nodes to track role shifts, format changes, and commercial upgrades.
- Analyze the four core layers: identity positioning, content/channel strategy, business model structure, and key decision turning points.
- Classify all findings as facts, inferences, or unknowns to maintain high research integrity and transparency.
- Generate the final deliverable, ranging from a one-page case brief to a comprehensive report with evidence tables.
OPC Case Research Setup
To utilize this skill, you must integrate the skill definition into your AI agent environment. Ensure that the associated reference documents and asset templates are accessible in the skill directory.
# Step 1: Clone or copy the opc-case-research skill files to your agent's skill path
# Step 2: Ensure the agent has access to the /references and /assets folders
# Step 3: Trigger the skill by providing a target name and desired depth (e.g., 'standard')
No complex API keys are required beyond the standard LLM access, as the skill relies on systematic processing of public information using search tools.
OPC Case Research Data Schema & Taxonomy
The skill organizes its output and internal data using a structured taxonomy to ensure all Openclaw Skills deliverables are consistent.
| Data Component | Format | Purpose |
|---|---|---|
| Source Map | List | Tracks first-party vs. third-party evidence origins |
| Timeline Table | CSV/Table | Documents role shifts and platform evolution |
| Evidence Slice | Appendix | Maps claims to specific evidence rows or bullet points |
| Four-Layer Analysis | Markdown | Breaks down Positioning, Content, Model, and Decisions |
| Replicability Analysis | Markdown | Extracts actionable takeaways for external application |
OPC Case Research Advanced Features
- Multi-depth execution modes (quick, standard, deep) to optimize for speed or detail.
- Source tiering system (A/B/C) to prioritize high-fidelity official data.
- Integrated replicability analysis to distinguish between unique luck and repeatable strategy.
- Automated evidence classification that highlights research gaps and uncertainties.
- Template-based report generation using pre-defined Markdown and CSV structures.
- Explicit separation of content strategy and business monetization layers for clearer insights.
SKILL.md
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