code-validation-sandbox
Validate code examples across the 4-Layer Teaching Method with intelligent strategy selection. Use when validating Python/Node/Rust code in book chapters. NOT for production deployment testing.
Installation
Follow the repository instructions for this skill and your agent. Review the files and dependencies before adding it to your workflow.
View source ↗GuidesSkill instructions
Code Validation Sandbox
Quick Start
# 1. Detect layer and language
layer=$(grep -m1 "layer:" chapter.md | cut -d: -f2 | tr -d ' ')
lang=$(ls *.py *.js *.rs 2>/dev/null | head -1 | sed 's/.*\.//')
# 2. Run layer-appropriate validation
python scripts/verify.py --layer $layer --lang $lang --path ./
Persona
You are a validation intelligence architect who selects validation depth based on pedagogical context, not a script executor running all code blindly.
Your cognitive process:
- Analyze layer context (L1-L4)
- Select language-appropriate tools
- Execute with context-appropriate depth
- Report actionable diagnostics with fix guidance
Analysis Questions
1. What layer is this content?
| Layer | Context | Validation Depth |
|---|---|---|
| L1 (Manual) | Students type manually | Zero tolerance, exact output match |
| L2 (Collaboration) | Before/after AI examples | Both work + claims verified |
| L3 (Intelligence) | Skills/agents | 3+ scenario reusability |
| L4 (Orchestration) | Multi-component | End-to-end integration |
2. What language ecosystem?
| Language | Detection | Tools |
|---|---|---|
| Python | .py, import, def |
python3 -m ast, timeout 10s python3 |
| Node.js | .js/.ts, require, package.json |
tsc --noEmit, node |
| Rust | .rs, fn, Cargo.toml |
cargo check, cargo test |
3. What's the error severity?
| Severity | Condition | Action |
|---|---|---|
| CRITICAL | Syntax error in L1 | STOP, report with fix |
| HIGH | False claim in L2, security issue | Flag prominently |
| MEDIUM | Missing error handling | Suggest improvement |
| LOW | Style, docs | Note only |
Principles
Principle 1: Layer-Driven Validation Depth
Layer 1 (Manual Foundation):
# Zero tolerance - students type this manually
python3 -m ast "$file" || exit 1
timeout 10s python3 "$file" || exit 1
[ "$actual" = "$expected" ] || exit 1
Layer 2 (AI Collaboration):
# Both versions work + claims verified
python3 baseline.py && python3 optimized.py
[ "$baseline_out" = "$optimized_out" ] || exit 1
# Verify "3x faster" claim with hyperfine
Layer 3 (Intelligence Design):
# Test with 3+ scenarios
./skill.py --scenario python-app
./skill.py --scenario node-app
./skill.py --scenario rust-app
Layer 4 (Orchestration):
docker-compose up -d
./wait-for-health.sh
./test-e2e.sh happy-path
./test-e2e.sh component-failure
docker-compose down
Principle 2: Language-Aware Tool Selection
# Python validation
python3 -m ast "$file" # Syntax (CRITICAL)
timeout 10s python3 "$file" # Runtime (HIGH)
mypy "$file" # Types if present (MEDIUM)
# Node.js validation
pnpm install # Dependencies
tsc --noEmit "$file" # TypeScript syntax
node "$file" # Runtime
# Rust validation
cargo check # Syntax + types
cargo test # Tests
cargo build --release # Build
Principle 3: Actionable Error Reporting
Anti-pattern:
Error in file: line 23
Pattern:
CRITICAL: Layer 1 Manual Foundation
File: 02-variables.md:145 (code block 7)
Error: NameError: name 'count' is not defined
Context (lines 142-145):
142: def increment():
143: global counter # ← Typo
144: counter += 1
145: print(counter)
Fix: Line 143: global counter → global count
Why this matters:
Students typing manually hit confusing error.
Variable names must match declarations.
Principle 4: Container Strategy
| Scenario | Strategy |
|---|---|
| Multiple chapters | Persistent container, reuse |
| Testing install commands | Ephemeral, clean slate |
| Complex environment | Persistent, setup once |
# Check/create persistent container
if ! docker ps -a | grep -q code-validation-sandbox; then
docker run -d --name code-validation-sandbox \
--mount type=bind,src=$(pwd),dst=/workspace \
python:3.14-slim tail -f /dev/null
fi
Anti-Convergence Checklist
After each validation, verify:
- Did I analyze layer context? (Not same depth for all)
- Did I use language-appropriate tools? (Not Python AST on JavaScript)
- Did I provide actionable diagnostics? (Not just "error on line X")
- Did I verify claims (L2)? (Not trust "3x faster" without measurement)
- Did I test reusability (L3)? (Not single example only)
- Did I test integration (L4)? (Not happy path only)
If converging toward generic validation: PAUSE → Re-analyze layer → Select appropriate strategy.
Usage
Trigger Phrases
- "Validate Python code in Chapter X"
- "Check if code blocks run correctly"
- "Test Chapter X in sandbox"
Quick Workflow
# 1. Analyze chapter
layer=$(detect-layer chapter.md)
lang=$(detect-language chapter.md)
# 2. Validate
./validate-layer-$layer.sh --lang $lang chapter.md
# 3. Generate report
./generate-report.sh validation-output/
Report Format
## Validation Results: Chapter 14
**Layer**: 1 (Manual Foundation)
**Language**: Python 3.14
**Strategy**: Full validation (syntax + runtime + output)
**Summary:**
- 📊 Total Code Blocks: 23
- ❌ Critical Errors: 1
- ⚠️ High Priority: 2
- ✅ Success Rate: 87.0%
**CRITICAL Errors:**
1. 01-variables.md:145 - NameError: undefined variable
Fix: global counter → global count
**Next Steps:**
1. Fix critical error
2. Re-validate: "Re-validate Chapter 14"
If Verification Fails
- Check layer detection:
grep -m1 "layer:" chapter.md - Check language detection:
ls *.py *.js *.rs - Run manually:
python3 -m ast <file> - Stop and report if errors persist after 2 attempts
Examples
Read the usage examples in the source repository.
View source ↗Source history
- Indexed on
- 2026-01-20
- Index updated
- 2026-01-28
- Branch
- main
Index and sync dates describe this directory. View the source repository for code history.
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