Automatically parses raw business queries alongside reference data to align metrics, dimensions, and filter conditions into structured spreadsheets.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install questionnaire
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 questionnaire 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 Business Query and Requirements Alignment?
The Business Query and Requirements Alignment template is a powerful solution designed to accelerate the early phases of BI dashboard design and data product development. By uploading multiple independent documents—including query logs, metric specifications, business glossaries, and data dictionaries—this asset utilizes Openclaw Skills to systematically extract, align, and organize complex technical requirements without manual labor.
By leveraging this automation with Openclaw Skills, engineering teams, analysts, and product managers can bridge the gap between raw business intent and underlying physical schemas. It ensures that every metric, dimension, and constraint requested by stakeholders is accurately identified and verified against data dictionaries or physical table structures before development begins.
Business Query and Requirements Alignment Use Cases
- Pre-development BI Dashboard Structuring: Instantly match incoming business inquiries to structural dimensions and metrics before designing dashboard layouts.
- Data Warehouse Synonyms Alignment: Resolve logical gaps by matching fuzzy, multi-departmental business terminology to standardized metrics.
- Schema and Requirements Validation: Use database DDL and metadata specs to verify if the business query filters map onto valid physical database columns.
- Automated Metric-Dimension Matrix Mapping: Instantly build relationship mapping matrices to trace exactly which metrics are evaluated along which dimensional slices.
How Business Query and Requirements Alignment Works
- Reference Resource Ingestion: The system loads the specified input documents, caching references like metric dimensions, business glossary logic, data dictionaries, and database schemas.
- Term Mapping Resolution: An internal index is structured, mapping business nouns, formulas (e.g., YoY, MoM), and hierarchical dimensions to their logical descriptions.
- Query Document Parsing: The core pipeline parses the primary question document row-by-row to detect user analytical intentions.
- Hierarchical Metric Matching: The algorithm traverses matches starting with the Metric and Dimension Spec down to DDL field searches, using business rules for synonym and calculations resolution.
- Dimension Extraction & Reverse Lookup: Identify dimensions directly from text or reverse-lookup metric members (e.g., mapping a specific country back to 'geography').
- Filter Parsing and Validation: Parse conditions (such as time scopes, TOP N, geographic zones) and optionally validate their column names against physical DDL schemas.
- Matrix Sheet Generation: Writes output directly into the source sheet columns and appends a 2D cross-matrix showing structural intersections with a checkmark indicator.
Business Query and Requirements Alignment Setup
Integrating this universal parser into your environment leverages native configurations of Openclaw Skills.
First, install the CLI runner or platform dependencies:
npm install -g @openclaw/cli
Next, place your reference sheets in your project directory and trigger the requirements analysis:
# Run the alignment tool with your queries and reference dictionary
openclaw run query-alignment --queries ./data/user_queries.xlsx --refs ./metadata/
Make sure your reference files match the naming conventions such as Metric Spec, Data Dictionary, or Business Knowledge to allow auto-detection.
Business Query and Requirements Alignment Data Schema & Taxonomy
The following lists represent how the workflow consumes optional input metadata and produces structured output:
Document Intake Taxonomy
| File Role | Accepted Files | Function in Extraction |
|---|---|---|
| Input Query | xlsx containing 'Query' column |
The source text containing questions to resolve |
| Metric Spec | xlsx or md specifying definitions |
Matches metric terms, formulas, and dimension attributes |
| Business Glossary | xlsx or md detailing context mappings |
Cross-reference rules, synonyms, default indicators, YoY metrics |
| Data Dictionary | Database field mappings | Map fields back to logical tables and attributes |
| DDL Schema | Table schema structures | Technical validation of extracted dimensions and filters |
Structured Alignment Outputs
- Corresponding Metric Column: A list of mapped metrics. Outputs an error warning ('Unidentified Metric') if the target remains unknown.
- Corresponding Dimension Column: A list of extracted dimension attributes mapped against the parsed metrics.
- Filter Conditions Column: Extracted constraints in standard
Field=Valueformatting separated by newlines. - Metric-Dimension 2D Matrix Sheet: A generated spreadsheet tab demonstrating intersections with clear checkmark indicators.
Business Query and Requirements Alignment Advanced Features
- Cross-Referencing Disambiguation Rules: Handles business jargon by mapping default implicit assumptions to precise metrics (e.g., standardizing general terms into distinct business definitions).
- Advanced Formula Breakdown: Automatically breaks compound business goals (like market share) down into basic arithmetic variables (numerator/denominator) for data execution.
- Intelligent Reverse Member Lookup: Identifies attributes by scanning specific enum members (e.g., matching 'USA' directly to a 'country_code' dimension).
- Failsafe DDL Checking: Cross-checks mapped filter conditions against real physical table columns to prevent database-level query compilation errors.
- Preservation of Styles: Directly mutates input spreadsheet cells, keeping pre-existing color schemes, fonts, margins, and column widths intact.
SKILL.md
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