heavy-review

Name: heavy-review
Availability: InStock
Author: kevinlasnh

Automate deployment plan review with multi-route evidence validation.

8|Updated Apr 21, 2026

Search Tags:#automation #deployment #audit #evidence #heavy-review

Ready to run

npx skills add https://github.com/kevinlasnh/sharing-studio --skill heavy-review

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: heavy-review
Source: https://github.com/kevinlasnh/sharing-studio/tree/main/projects/agent-workflows/skills/heavy-review
Command: npx skills add https://github.com/kevinlasnh/sharing-studio --skill heavy-review

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

Heavy deployment reviews are error-prone and time-consuming due to scattered evidence and manual coordination. This skill orchestrates a rigorous, multi-path review process that collects, validates, and consolidates deployment-plan evidence into a single, auditable outcome.

Core Features & Use Cases

Structured plan extraction: reads the latest deployment-plan.md, identifies target deployment goals, key gaps, and risk factors.
Evidence routing orchestration: spawns subagents to verify web and source routes in parallel when available, with deterministic plan_sha256 tracking.
Inline remediation guidance: after review, surfaces concrete changes that can be inline-edited into the same plan document.

Quick Start

Trigger heavy-review when a deployment plan is ready for formal review, and the system will locate the latest deployment-plan.md, run checks, and present a structured result.

Frequently Asked Questions about heavy-review

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I automate deployment plan review and evidence validation?▼

Automating deployment plan review requires collecting and consolidating scattered evidence. This skill reads deployment-plan.md, identifies target goals and gaps, then routes parallel web and source checks via subagents to produce a structured auditable report with deterministic plan_sha256 tracking.

What is multi-route evidence validation for deployment plans?▼

Multi-route evidence validation verifies deployment plans by spawning subagents to check web and source paths. It consolidates findings into a single auditable outcome with deterministic plan_sha256 tracking, returning a structured report suitable for R2 and R3 review stages.

How do I extract and review risks from a deployment-plan.md file?▼

Reviewing risks from deployment-plan.md involves structured extraction of target deployment goals, key gaps, and risk factors. The system then orchestrates parallel evidence validation and surfaces concrete inline remediation guidance directly editable within the plan document.

Can I get inline remediation guidance after a deployment audit?▼

Yes, inline remediation guidance is generated after the deployment audit. The review process surfaces concrete changes that can be directly inline-edited into the same deployment-plan.md document, ensuring evidence validation and fixes remain consolidated.

Does automated deployment review work without external dependencies?▼

Yes, automated deployment review works without external dependencies. The skill orchestrates multi-route evidence validation and parallel subagent checks internally, requiring only a deployment-plan.md file to produce a structured review report with deterministic plan_sha256 tracking.