An AI-powered requirement analysis expert leveraging the Tianlong Engine V7.4 to provide deep deconstruction and critical evaluation of complex project needs.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install tianlong-report
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 tianlong-report 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 tianlong-analyst?
tianlong-analyst is a sophisticated analytical tool designed to help developers and product managers look beyond surface-level requests. By utilizing the Tianlong Engine V7.4, this skill specializes in requirement deconstruction, helping users identify the root causes of problems and evaluate the true essence of any project. It is a vital addition to any Openclaw Skills collection for those who prioritize logic, first-principles thinking, and structured decision-making.
The skill stands out with its high critical thinking score of 0.96, ensuring that the generated reports are not just summaries but deep dives into feasibility and strategy. It effectively bridges the gap between a vague idea and a technical roadmap by identifying target user personas, usage scenarios, and potential risks before development even begins.
tianlong-analyst Use Cases
- Validating startup ideas by separating surface-level wants from actual market needs.
- Performing technical architecture assessments to support complex decision-making processes.
- Conducting pre-project feasibility studies to evaluate risks and costs before resource allocation.
- Assisting in professional career or investment decisions through structured logical reasoning.
How tianlong-analyst Works
- The user initiates the analysis by providing a requirement description using the /tianlong-analyst command.
- The system deconstructs the input to distinguish between the stated surface requirement and the underlying real requirement.
- A complexity assessment is performed, categorizing the project into a traffic light system (Green, Yellow, or Red) based on risk and execution difficulty.
- The engine applies critical thinking frameworks, including first principles analysis, incentive analysis, and second-order thinking.
- The skill generates a comprehensive structured report featuring action items, decision points, and risk warnings.
tianlong-analyst Setup
To use this analyst within your Openclaw Skills environment, ensure your agent has access to the Tianlong Engine V7.4 core. You can trigger the analysis directly via the command line interface:
# Basic usage syntax
/tianlong-analyst <requirement_description>
# Example command
/tianlong-analyst I want to build an AI writing assistant
tianlong-analyst Data Schema & Taxonomy
The skill organizes its analytical output into a clear, hierarchical taxonomy. This ensures that users can quickly navigate from high-level summaries to deep critical insights. The output structure includes:
| Section | Content Details |
|---|---|
| Requirement Deconstruction | Surface vs. Real needs, user profiling, and scenario identification. |
| Complexity Matrix | Level-based assessment (Green/Yellow/Red) with specific execution standards. |
| Critical Thinking Logic | First principles, incentive analysis, and asymmetric return evaluation. |
| Actionable Roadmap | Categorized tasks: Immediate Execution, Decision Required, and Risk Warnings. |
tianlong-analyst Advanced Features
- High-precision critical thinking engine with a validated score of 0.96 for reliable analysis.
- Automated traffic light complexity assessment to streamline project prioritization.
- Multi-dimensional logic推演 including second-order thinking and asymmetric return modeling.
- Structured MVP (Minimum Viable Product) guidance for rapid validation of core functions.
SKILL.md
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