39-agent-skills-mcp-code-execution

Build Script-Execution Skill

You've learned the pattern (Lesson 5): write code from specification → execute it → analyze errors → iterate. Now you're going to build a skill that orchestrates this loop autonomously.

But here's what makes this different from following a tutorial: You'll specify what problem you're solving FIRST, then let AI help you build the skill while you validate each decision. You're not just learning a pattern—you're learning to think about error recovery, convergence criteria, and edge cases the way production systems demand.

Step 1: Write Your Specification

Before touching any skill code, write a specification for the problem you're solving. You'll use a CSV data processing task because it's concrete and has natural edge cases.

Choose one of these:

• CSV Analysis: Analyze customer or sales data for patterns
• CSV Transformation: Clean and restructure messy CSV data
• CSV Aggregation: Group data by dimensions and calculate metrics

Or define your own data processing task.

Your Specification

Write this to a file (skill-spec.md) or document:

# CSV Analysis Skill Specification

## Intent
[What does this skill do? Be specific about the business problem it solves]

## Input
- data_file: [type and format, e.g., "CSV with columns: customer_id, purchase_date, amount"]
- parameters: [what configuration does skill accept?]

## Output
- format: [JSON, CSV, report?]
- required_fields: [exact fields that must be in output]
- validation_rules: [how to verify output is correct]

## Success Criteria
- All data processed without loss
- Output format exactly matches specification
- Edge cases handled gracefully (malformed rows, missing values, etc.)
- Execution completes within 30 seconds

## Edge Cases to Handle
- [Case 1: e.g., "Empty CSV file"]
- [Case 2: e.g., "Missing column header"]
- [Case 3: e.g., "Non-numeric values in amount field"]

Key principle: Your specification must be complete enough that AI can generate correct code without additional context. If your spec is vague, the generated code will be equally vague.