intent-solutions-io/org-verification-pipeline
000-docs/000a-planned-skills/templates/verification-pipeline/skill-package/SKILL.md
Produces verified datasets, verified evaluation results, and a deployable contract bundle for a workflow. Use when you need provable correctness at data and evaluation boundaries. Trigger with 'verify workflow', 'validate contract', or 'run verification pipeline'.
$ install --global
skillsauthnpx skillsauth add intent-solutions-io/plugins-nixtla org-verification-pipelineInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
Security Scan Results
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
3
Scanners Passed
9
Scanners in report
Clean
TrivyContainer and dependency vulnerability scanner
95%
Clean
SemgrepStatic code analysis for vulnerabilities
95%
Clean
mcp-scan (Snyk)Model Context Protocol security validation
95%
Skipped
Snyk (dep)Open source security scanning
50%
Skipped
Socket.devSupply chain security analysis
50%
Skipped
VirusTotalMulti-engine malware detection
50%
Skipped
CrowdStrikeAdvanced threat intelligence
50%
Skipped
OSV-ScannerOpen Source Vulnerability database check
50%
Skipped
OWASP Dep-Check
50%
Last scanned: Apr 5, 2026, 11:13 PM15.0s15 files scanned
SKILL.md
- name:
- org-verification-pipeline
- description:
- Produces verified datasets, verified evaluation results, and a deployable contract bundle for a workflow. Use when you need provable correctness at data and evaluation boundaries. Trigger with 'verify workflow', 'validate contract', or 'run verification pipeline'.
- allowed-tools:
- Read,Write,Glob,Grep,Bash(python:*),Bash(jq:*)
- version:
- 0.1.0
- author:
- Your Team <[email protected]>
- license:
- MIT
Verification Pipeline (5-Phase)
Produce verified artifacts (data, metrics, contracts) using a 5-phase gated workflow with deterministic scripts.
Overview
This skill runs a strict pipeline:
- Phase 1 maps raw inputs to a canonical contract
- Phase 2 audits data quality deterministically
- Phase 3 produces a runnable evaluation plan
- Phase 4 runs a reproducible evaluation and computes metrics
- Phase 5 produces a deployable contract bundle and validates examples
Prerequisites
- Python 3.11+
- Repo dependencies installed
- Input dataset available (CSV/Parquet/JSON) and a target contract defined
Instructions
- Create a run directory under
reports/<project>/<timestamp>/. - Run phases in order using agents in
agents/and procedures inreferences/. - After each phase:
- validate the returned JSON contract
- verify
report_pathexists
- Run verification scripts (must pass) before continuing:
- Phase 1:
{baseDir}/scripts/verify_schema.py - Phase 2:
{baseDir}/scripts/verify_integrity.pyand{baseDir}/scripts/verify_frequency.py - Phase 4:
{baseDir}/scripts/run_backtest.py - Phase 5:
{baseDir}/scripts/verify_api_examples.sh
- Phase 1:
Output
reports/<project>/<timestamp>/0X-*.md: evidence reportsreports/<project>/<timestamp>/quality.json: quality summaryreports/<project>/<timestamp>/metrics.json: evaluation metricsreports/<project>/<timestamp>/contract/**: deployable contract bundle
Error Handling
-
Error: Phase JSON is invalid / missing keys
Solution: Re-run the phase and ensure strict JSON output contract is met. -
Error: Verification script fails
Solution: Treat script output as ground truth; update mapping, data, or plan until scripts pass.
Examples
# Example: run schema verification (Phase 1)
python {baseDir}/scripts/verify_schema.py \
--input data/raw.csv \
--schema references/00-canonical-schema.json \
--out reports/example/2025-01-01T00-00-00Z/quality.json
Resources
- Procedures:
{baseDir}/references/ - Agents:
{baseDir}/agents/ - Scripts:
{baseDir}/scripts/
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