analytics-scoping
Define the scope of analytics efforts by identifying relevant metrics, data sources, and analysis approaches. Use when framing pilot analysis questions, selecting KPIs, or aligning data feeds to business objectives and stakeholder needs.
Best use case
analytics-scoping is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Define the scope of analytics efforts by identifying relevant metrics, data sources, and analysis approaches. Use when framing pilot analysis questions, selecting KPIs, or aligning data feeds to business objectives and stakeholder needs.
Teams using analytics-scoping should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/analytics-scoping/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How analytics-scoping Compares
| Feature / Agent | analytics-scoping | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Define the scope of analytics efforts by identifying relevant metrics, data sources, and analysis approaches. Use when framing pilot analysis questions, selecting KPIs, or aligning data feeds to business objectives and stakeholder needs.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Analytics Scoping ## Overview [TODO: 1-2 sentences explaining what this skill enables] ## Structuring This Skill [TODO: Choose the structure that best fits this skill's purpose. Common patterns: **1. Workflow-Based** (best for sequential processes) - Works well when there are clear step-by-step procedures - Example: DOCX skill with "Workflow Decision Tree" -> "Reading" -> "Creating" -> "Editing" - Structure: ## Overview -> ## Workflow Decision Tree -> ## Step 1 -> ## Step 2... **2. Task-Based** (best for tool collections) - Works well when the skill offers different operations/capabilities - Example: PDF skill with "Quick Start" -> "Merge PDFs" -> "Split PDFs" -> "Extract Text" - Structure: ## Overview -> ## Quick Start -> ## Task Category 1 -> ## Task Category 2... **3. Reference/Guidelines** (best for standards or specifications) - Works well for brand guidelines, coding standards, or requirements - Example: Brand styling with "Brand Guidelines" -> "Colors" -> "Typography" -> "Features" - Structure: ## Overview -> ## Guidelines -> ## Specifications -> ## Usage... **4. Capabilities-Based** (best for integrated systems) - Works well when the skill provides multiple interrelated features - Example: Product Management with "Core Capabilities" -> numbered capability list - Structure: ## Overview -> ## Core Capabilities -> ### 1. Feature -> ### 2. Feature... Patterns can be mixed and matched as needed. Most skills combine patterns (e.g., start with task-based, add workflow for complex operations). Delete this entire "Structuring This Skill" section when done - it's just guidance.] ## [TODO: Replace with the first main section based on chosen structure] [TODO: Add content here. See examples in existing skills: - Code samples for technical skills - Decision trees for complex workflows - Concrete examples with realistic user requests - References to scripts/templates/references as needed] ## Resources (optional) Create only the resource directories this skill actually needs. Delete this section if no resources are required. ### scripts/ Executable code (Python/Bash/etc.) that can be run directly to perform specific operations. **Examples from other skills:** - PDF skill: `fill_fillable_fields.py`, `extract_form_field_info.py` - utilities for PDF manipulation - DOCX skill: `document.py`, `utilities.py` - Python modules for document processing **Appropriate for:** Python scripts, shell scripts, or any executable code that performs automation, data processing, or specific operations. **Note:** Scripts may be executed without loading into context, but can still be read by Codex for patching or environment adjustments. ### references/ Documentation and reference material intended to be loaded into context to inform Codex's process and thinking. **Examples from other skills:** - Product management: `communication.md`, `context_building.md` - detailed workflow guides - BigQuery: API reference documentation and query examples - Finance: Schema documentation, company policies **Appropriate for:** In-depth documentation, API references, database schemas, comprehensive guides, or any detailed information that Codex should reference while working. ### assets/ Files not intended to be loaded into context, but rather used within the output Codex produces. **Examples from other skills:** - Brand styling: PowerPoint template files (.pptx), logo files - Frontend builder: HTML/React boilerplate project directories - Typography: Font files (.ttf, .woff2) **Appropriate for:** Templates, boilerplate code, document templates, images, icons, fonts, or any files meant to be copied or used in the final output. --- **Not every skill requires all three types of resources.**
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