How do I install the Temper skill?

Run npx skillmds@latest add sharpdeveye/temper in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Temper safe to use?

This skill has not completed SkillMD's automated safety review yet. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Temper?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Temper free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Temper?

sharpdeveye (@sharpdeveye) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Temper by sharpdeveye — Agent Skill

Name: Temper
Author: sharpdeveye

File contents

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:

Is this solving a problem we actually have? (not "might have")
Is this the simplest solution that works?
Would removing this break anything? (if not, remove it)
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

---name: temperdescription: Use when the workflow feels over-engineered, has premature optimizations, unnecessary abstraction layers, or complexity beyond actual requirements.---## MANDATORY PREPARATIONInvoke /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 TestFor 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**```textOVER-ENGINEERED: User → Classifier → Router → Specialist → Formatter → Checker (6 components)TEMPERED: User → Single Agent with good prompt (1 component, same quality)```**Remove Premature Abstraction**```textOVER-ENGINEERED: class AgentOrchestrator with 5 strategy interfacesTEMPERED: async function runWorkflow(input) — direct, readable```**Simplify Configuration**```textOVER-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 StepAfter 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

Frequently asked questions

Temper