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Skill

/temper

Use when the workflow feels over-engineered, has premature optimizations, unnecessary abstraction layers, or complexity beyond actual requirements.

From plugin
maestro
41125 skills
Install
$ npx -y skills add sharpdeveye/maestro --skill temper --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/temper

Context preview

The summary Claude sees to decide when to auto-load this skill.

Use when the workflow feels over-engineered, has premature optimizations, unnecessary abstraction layers, or complexity beyond actual requirements.

SKILL.md

temper.SKILL.md
name: temper
description: "Use when the workflow feels over-engineered, has premature optimizations, unnecessary abstraction layers, or complexity beyond actual requirements."
argument-hint: "[target]"
category: enhancement
version: 2.0.0
user-invocable: true

MANDATORY PREPARATION

Invoke /agent-workflow — it contains workflow principles, anti-patterns, and the **Context Gathering Protocol**. Follow the protocol before proceeding — if no workflow context exists yet, you MUST run /teach-maestro first. Consult the agent-architecture reference in the agent-workflow skill for topology patterns and when multi-agent is justified.

---

Pull back from over-engineering. The most common mistake isn't building too little — it's building too much.

Over-Engineering Detection

**Signs you've over-engineered:**

  • Multi-agent for a single-agent problem
  • Premature optimization before you have performance data
  • Abstraction layers with one implementation
  • Configuration for things that never change
  • Evaluation loops on non-critical outputs
  • Framework before features

The Complexity Test

For each component:

1. **Is this solving a problem we actually have?** (not "might have") 2. **Is this the simplest solution that works?** 3. **Would removing this break anything?** (if not, remove it) 4. **Can someone new understand this in 5 minutes?** (if not, simplify)

Tempering Strategies

**Collapse Unnecessary Agents**

OVER-ENGINEERED: User → Classifier → Router → Specialist → Formatter → Checker (6 components)
TEMPERED: User → Single Agent with good prompt (1 component, same quality)

**Remove Premature Abstraction**

OVER-ENGINEERED: class AgentOrchestrator with 5 strategy interfaces
TEMPERED: async function runWorkflow(input) — direct, readable

**Simplify Configuration**

OVER-ENGINEERED: config.yaml (200 lines, 47 params, 3 inheritance levels)
TEMPERED: config.yaml (20 lines, essential params only, sensible defaults)

What NOT to Temper

  • Error handling — essential, not overhead
  • Logging — saves you when things go wrong
  • Input validation — prevents cascading failures
  • Core guardrails — safety is non-negotiable
  • The golden test set — how you know it still works

Recommended Next Step

After tempering, run `/evaluate` to confirm quality is preserved, or `/diagnose` for a full health check.

**NEVER**:

  • Temper without measuring output quality before and after
  • Remove error handling in the name of simplicity
  • Simplify below the level of correctness
  • Remove features users actively rely on
Read more
Ships withmaestro

Workflow fluency for AI coding agents. 1 core skill · 25 commands · 7 domain references · memory layer · audit trail — works across Cursor, Claude Code, Gemini CLI, Copilot, and 6 more.

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TypeScript
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MIT
License
3mo ago
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4mo ago
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Repo: sharpdeveye/maestro