meta-implement

Automate YAML-driven implementation of /meta-learn improvements with dry-run checks and rollback.

2|3|Updated Oct 20, 2025
One-click install
npx skills add https://github.com/psd401/psd-claude-coding-system --skill meta-implement
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: meta-implement
Source: https://github.com/psd401/psd-claude-coding-system/tree/main/plugins/psd-claude-coding-system/skills/meta-implement
Command: npx skills add https://github.com/psd401/psd-claude-coding-system --skill meta-implement

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill enables teams to automatically implement high-confidence improvements generated by /meta-learn while ensuring safety through dry-run checks, backups, and rollback mechanisms. It eliminates manual, error-prone adoption of optimizations and accelerates secure deployment.

Core Features & Use Cases

  • Dry-run Safety: Simulates all changes before applying them, preventing unintended side effects.
  • Branch-based Implementation: Creates a dedicated implementation branch and preserves the mainline.
  • Plan-driven Execution: Executes a YAML-defined implementation plan including file creates/modifications, command updates, and agent creation.
  • Validation-first Rollback: Runs tests and validation; automatically rolls back if failures occur and opens human reviews via PRs.
  • Use Case: As a development team, you can auto-apply high-confidence improvements from /meta-learn in a reversible, auditable way.

Quick Start

Run: 1) Inspect high-confidence suggestions with /meta-learn. 2) Dry-run the implementation with /meta-implement meta-learn-<id> --dry-run. 3) Apply changes with /meta-implement meta-learn-<id> after successful dry-run.

Frequently Asked Questions about meta-implement

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

FAQPage Schema
How do I safely auto-implement improvements without risking production?

Auto-implement uses dry-run checks to simulate all changes before applying them, preventing unintended side effects. It creates a dedicated branch, runs validation tests, and automatically rolls back if failures occur, keeping your mainline protected.

What's the workflow for applying improvements generated by meta-learn?

Inspect suggestions with meta-learn, run a dry-run with meta-implement to simulate changes, review the plan, then apply with meta-implement to execute the YAML-driven implementation, validation, and rollback if needed.

Can auto-implementation roll back if validation fails?

Yes. Auto-implement runs tests after applying changes and automatically rolls back if validation fails, then opens a human review via PR so your team can assess what went wrong.

Does auto-implement preserve my main branch during implementation?

Yes. Auto-implement creates a dedicated implementation branch, keeping your mainline intact. Changes only merge after passing validation, ensuring your production code stays stable.

What security checks does auto-implementation enforce?

Auto-implement enforces security validation, checks dependencies, and requires human review before merging. It orchestrates branch creation, file changes, command execution, and testing under a YAML-driven plan.

Do I need to manually review changes before auto-implement applies them?

You can inspect and dry-run changes first to verify safety. Auto-implement enforces human review before merging, and opens PRs if validation fails, ensuring human oversight at critical gates.