002-workspaces/test-harness-lab/skills/nixtla-release-validation/SKILL.md
Multi-phase release validation workflow for nixtla. Analyzes git changes, predicts test impact, assesses risk, runs pytest verification, provides go/no-go recommendation. Trigger: "validate release", "run release validation", "check release readiness"
npx skillsauth add intent-solutions-io/plugins-nixtla nixtla-release-validationInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
Automated pre-release validation using multi-phase test harness pattern with empirical verification.
Validate nixtla releases (e.g., v1.7.0 → v1.8.0) before shipping by analyzing changes, predicting impact, running tests, and providing evidence-based go/no-go recommendation.
This workflow implements the 5-phase validated workflow pattern:
Phase 4 is the critical phase - it runs actual scripts to verify Phase 2 predictions.
jq for JSON processing002-workspaces/test-harness-lab/skills/nixtla-release-validation/reports/cd 002-workspaces/test-harness-lab/skills/nixtla-release-validation
TIMESTAMP=$(date +%Y%m%d_%H%M%S)
SESSION_DIR="reports/${TIMESTAMP}"
mkdir -p "${SESSION_DIR}"
Task: Spawn Phase 1 agent
Input JSON:
{
"session_dir": "<SESSION_DIR>",
"from_version": "v1.7.0",
"to_version": "v1.8.0",
"repo_path": "/home/jeremy/000-projects/nixtla"
}
Expected Output: <SESSION_DIR>/phase1-change-analysis.json
{
"metadata": {
"phase": 1,
"timestamp": "2025-12-22T17:00:00Z"
},
"changes": {
"changed_files": ["src/forecast.py", "tests/test_forecast.py"],
"changed_apis": ["forecast()", "fit()"],
"breaking_changes": ["forecast() now requires 'freq' parameter"],
"new_features": ["Added anomaly detection"]
}
}
Task: Spawn Phase 2 agent
Input JSON:
{
"session_dir": "<SESSION_DIR>",
"phase1_output": "<SESSION_DIR>/phase1-change-analysis.json"
}
Expected Output: <SESSION_DIR>/phase2-test-predictions.json
{
"metadata": {
"phase": 2,
"timestamp": "2025-12-22T17:05:00Z"
},
"test_predictions": [
{
"change": "Modified forecast() signature",
"affected_tests": ["test_forecast_basic", "test_forecast_with_exog"],
"reason": "Function signature changed, existing calls will fail"
}
]
}
Task: Spawn Phase 3 agent
Input JSON:
{
"session_dir": "<SESSION_DIR>",
"phase1_output": "<SESSION_DIR>/phase1-change-analysis.json",
"phase2_output": "<SESSION_DIR>/phase2-test-predictions.json"
}
Expected Output: <SESSION_DIR>/phase3-risk-assessment.json
{
"metadata": {
"phase": 3,
"timestamp": "2025-12-22T17:10:00Z"
},
"risk_categories": {
"high_risk": ["forecast() signature change - breaking"],
"medium_risk": ["New anomaly detection - needs testing"],
"low_risk": ["Documentation updates"]
},
"go_no_go": "pending"
}
Task: Run verification script, compare predictions vs reality
Script: scripts/analyze_test_results.sh
bash scripts/analyze_test_results.sh \
"/home/jeremy/000-projects/nixtla" \
"${SESSION_DIR}"
Expected Output: <SESSION_DIR>/phase4-verification-report.json
{
"metadata": {
"phase": 4,
"script": "analyze_test_results.sh",
"timestamp": "2025-12-22T17:15:00Z"
},
"results": {
"tests_run": 145,
"tests_passed": 142,
"tests_failed": 3,
"coverage_pct": 87.5,
"failed_tests": ["test_forecast_basic", "test_forecast_with_exog"]
},
"prediction_comparison": {
"predictions_confirmed": ["test_forecast_basic - FAILED as predicted"],
"predictions_revised": [],
"unexpected_failures": ["test_hierarchical - not predicted"]
}
}
Task: Spawn Phase 5 agent
Input JSON:
{
"session_dir": "<SESSION_DIR>",
"phase3_output": "<SESSION_DIR>/phase3-risk-assessment.json",
"phase4_output": "<SESSION_DIR>/phase4-verification-report.json"
}
Expected Output: <SESSION_DIR>/phase5-final-recommendation.json
{
"metadata": {
"phase": 5,
"timestamp": "2025-12-22T17:20:00Z"
},
"recommendation": "no-go",
"blockers": [
"3 test failures must be fixed before release",
"forecast() breaking change needs migration guide"
],
"release_notes": "...",
"migration_steps": [...]
}
Create summary markdown report:
cat > "${SESSION_DIR}/RELEASE-VALIDATION-SUMMARY.md" <<EOF
# Release Validation Summary
**Release**: v1.7.0 → v1.8.0
**Date**: $(date)
**Recommendation**: NO-GO
## Test Results
- Tests Run: 145
- Passed: 142
- Failed: 3
## Blockers
1. forecast() breaking change needs migration guide
2. 3 test failures must be addressed
## Next Steps
1. Fix test_forecast_basic
2. Fix test_forecast_with_exog
3. Fix test_hierarchical
4. Write migration guide for forecast() changes
5. Re-run validation
EOF
Structured Outputs:
phase1-change-analysis.json - Git changes analyzedphase2-test-predictions.json - Impact predictionsphase3-risk-assessment.json - Risk categoriesphase4-verification-report.json - Actual test resultsphase5-final-recommendation.json - Go/no-go decisionRELEASE-VALIDATION-SUMMARY.md - Human-readable summaryEvidence Trail: All outputs in timestamped session directory.
If Phase 1-3 fail: Check JSON syntax, file paths, git tags exist.
If Phase 4 fails:
scripts/analyze_test_results.sh exists and is executableIf Phase 5 fails: Check Phase 3-4 JSON outputs exist and are valid.
Validation Failures: Each phase must write valid JSON to expected path before next phase runs.
cd 002-workspaces/test-harness-lab/skills/nixtla-release-validation
SESSION_DIR="reports/$(date +%Y%m%d_%H%M%S)"
mkdir -p "${SESSION_DIR}"
# Phase 1-5: Spawn agents sequentially
# Phase 4: Run verification script
bash scripts/analyze_test_results.sh /home/jeremy/000-projects/nixtla "${SESSION_DIR}"
# Check final recommendation
cat "${SESSION_DIR}/phase5-final-recommendation.json" | jq '.recommendation'
SESSION_DIR="reports/test_v1.6_to_v1.7"
mkdir -p "${SESSION_DIR}"
# Run phases with historical release
# Compare predictions vs actual (known outcome)
002-workspaces/test-harness-lab/reference-implementation/scripts/analyze_test_results.shagents/phase_*.mdtools
This skill assists with managing database sharding strategies. It is activated when the user needs to implement horizontal database sharding to scale beyond single-server limitations. The skill supports designing sharding strategies, distributing data across multiple database instances, and implementing consistent hashing, automatic rebalancing, and cross-shard query coordination. Use this skill when the user mentions "database sharding", "sharding implementation", "scale database", or "horizontal partitioning". The plugin helps design and implement sharding for high-scale applications.
tools
This skill enables Claude to perform comprehensive database security scans using the database-security-scanner plugin. It is triggered when the user requests a security assessment of a database, including identifying vulnerabilities like weak passwords, SQL injection risks, and insecure configurations. The skill leverages OWASP guidelines to ensure thorough coverage and provides remediation suggestions. Use this skill when the user asks to "scan database security", "check database for vulnerabilities", "perform OWASP compliance check on database", or "assess database security posture". The plugin supports PostgreSQL and MySQL.
testing
This skill enables Claude to design and visualize database schemas. It leverages normalization guidance (1NF through BCNF), relationship mapping, and ERD generation to create efficient and well-structured databases. Use this skill when the user requests to "design a database schema", "create a database model", "generate an ERD", "normalize a database", or needs help with "database design best practices". The skill is triggered by terms like "database schema", "ERD diagram", "database normalization", and "relational database design".
tools
This skill enables Claude to manage database replication, failover, and high availability configurations using the database-replication-manager plugin. It is designed to assist with tasks such as setting up master-slave replication, configuring automatic failover, monitoring replication lag, and implementing read scaling. Use this skill when the user requests help with "database replication", "failover configuration", "high availability", "replication lag", or "read scaling" for databases like PostgreSQL or MySQL. The plugin facilitates both physical and logical replication strategies.