Engineering discipline skills: Rob Pike's optimization rules and systematic debugging methodology
npx claudepluginhub tmdgusya/engineering-disciplineEngineering discipline skills: optimization rules, systematic debugging, AI slop cleanup, and implementation guardrails
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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
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clarification ─── resolve ambiguity, explore codebase
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|── 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
| |── ...
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|── 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.