SKILL for engineering-discipline
npx skills add https://github.com/tmdgusya/engineering-discipline --skill systematic-debuggingInstale esta skill com a CLI e comece a usar o fluxo de trabalho SKILL.md em seu espaço de trabalho.
Engineering discipline skills for AI coding agents. Works with Claude Code, Gemini CLI, OpenCode, Codex, and Cursor.
Skills chain together to handle tasks from vague request to verified implementation:
User request
|
clarification ─── resolve ambiguity, explore codebase
|
|── Complexity Assessment (auto-routing)
| |
| |── Simple (score 5-8)
| | |
| | plan-crafting ─── create executable plan
| | |
| | run-plan ─── worker-validator execution loop
| | |
| | review-work ─── information-isolated verification
| |
| |── Complex (score 9-15)
| |
| milestone-planning ─── 5 parallel reviewers + synthesis
| |
| long-run ─── multi-day orchestrator
| |── M1: plan-crafting → run-plan → review-work → checkpoint
| |── M2: plan-crafting → run-plan → review-work → checkpoint
| |── ...
|
|── karpathy ─── implementation guardrails (before/during coding)
|── clean-ai-slop ─── post-generation AI code cleanup
|── simplify ─── post-implementation code quality pass
|── systematic-debugging ─── reproduce-first bug fixing
|── rob-pike ─── measurement-driven optimization
You don't need to memorize this. Each skill activates automatically based on trigger phrases and context.
Resolves vague requests into well-defined work scopes through iterative Q&A + parallel codebase exploration. Outputs a Context Brief with automatic complexity routing.
Triggers on: "I want to...", "I need...", "let's build...", or any request where scope isn't immediately clear.
Creates executable multi-step implementation plans from a clear scope. Every step contains actual code — no placeholders allowed.
Triggers on: "plan this", "create a plan", or after clarification completes with a Simple verdict.
Executes plans using worker-validator pairs. Workers implement, validators verify independently with zero knowledge of the worker's approach.
Triggers on: "run the plan", "execute the plan", or after plan-crafting completes.
Information-isolated post-execution verification. Reads only the plan document and the codebase — receives no execution logs or worker output.
Triggers on: "review the work", "verify the implementation", or after run-plan completes.
Reviews changed code through three parallel agents (reuse, quality, efficiency), then fixes any issues found.
Triggers on: "simplify", "clean up the code", "review the changes".
For complex tasks that span multiple days.
Spawns 5 independent reviewer agents in parallel — feasibility, architecture, risk, dependency, user value — then synthesizes their findings into an optimized milestone dependency DAG.
Triggers on: "plan milestones", "break this into milestones", "ultraplan", or after clarification with a Complex verdict (score 9-15).
Key features:
Orchestrates multi-day execution. Each milestone passes through plan-crafting, run-plan, review-work with checkpoint/recovery.
Triggers on: "long run", "start long run", "execute milestones".
Key features:
Preventive guardrails for code implementation — enforces surgical changes, assumption verification, and scope discipline before and during coding.
Triggers on: Before implementing features, modifying code, or when generating code without reading existing context first.
Corrective cleanup of AI-generated code. Removes LLM-specific patterns (over-commenting, unnecessary abstractions, defensive paranoia, verbose naming, filler) while preserving behavior. Regression-tests-first, single-smell-pass discipline.
Triggers on: "clean up", "deslop", "slop", "clean AI code", or after any significant generation session.
A decision framework that prevents premature optimization and enforces measurement-driven development.
Triggers on: "optimize", "slow", "performance", "bottleneck", "speed up", "make faster", "too slow"
Strict debugging workflow: reproduce-first, root-cause-first, failing-test-first.
Triggers on: Any bug, test failure, or unexpected behavior.
Reference guides:
After installation, just describe what you want to do:
/plugin marketplace add tmdgusya/engineering-discipline
/plugin install engineering-discipline
gemini extensions install https://github.com/tmdgusya/engineering-discipline
Install from the plugin marketplace, or:
/add-plugin engineering-discipline
npx skills add tmdgusya/engineering-discipline
Or install globally (available across all projects):
npx skills add tmdgusya/engineering-discipline -g
See Codex install guide for details.
Add to your opencode.json:
{
"plugin": ["engineering-discipline@git+https://github.com/tmdgusya/engineering-discipline.git"]
}
See OpenCode install guide for details.
Start a new session and mention a performance concern or a bug. The relevant skill should activate automatically.
This plugin is listed in the Claude Code plugin marketplace.
/plugin marketplace add tmdgusya/engineering-discipline
/plugin install engineering-discipline
Update .claude-plugin/marketplace.json with a new version and push to the repository. The marketplace entry pulls metadata from that file.
MIT