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Agent skill

Temper

by sharpdeveye in sharpdeveye/maestro

A skill your agent uses when the workflow feels over-engineered, has premature optimizations, unnecessary abstraction layers, or complexity beyond actual requirements.

MITAuto-check passed

Install Temper

skills CLI
$ npx skills add sharpdeveye/maestro --skill temper -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install sharpdeveye/maestro temper --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/sharpdeveye/maestro.git skills-src && mkdir -p .claude/skills && cp -r skills-src/source/skills/temper .claude/skills/temper && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
temper
GitHub stars
592
Token cost
~649 tokens
SKILL.md length
240 words
Files
1
Skills in repo
25
Repo updated
First seen
Licence
MIT

At a glance

A skill your agent uses when the workflow feels over-engineered, has premature optimizations, unnecessary abstraction layers, or complexity beyond actual requirements.

  • Works in 4 steps: Is this solving a problem we actually… → Is this the simplest solution that works? → Would removing this break anything? (if… → …
  • The workflow feels over-engineered
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
  • Has premature optimizations

What it does

Temper is an agent skill from sharpdeveye/maestro. Use when the workflow feels over-engineered, has premature optimizations, unnecessary abstraction layers, or complexity beyond actual requirements.

Its SKILL.md is about 650 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

The repository describes itself as: 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… The licence is MIT.

When your agent uses it

  • The workflow feels over-engineered
  • Has premature optimizations
  • Unnecessary abstraction layers
  • Complexity beyond actual requirements

Example prompts

  • “/temper”

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

  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)

What it can do on your machine

Read from SKILL.md and the folder at commit 00f9115. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Temper loads about 649 tokens when it runs. Until then it costs about 39 tokens; SKILL.md has 240 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~39
When it runs · the whole SKILL.md, loaded when a task matches
~649

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from sharpdeveye/maestro at commit 00f9115, republished under its MIT licence (© sharpdeveye). 240 words, ~649 tokens.

Download SKILL.mdSave it as .claude/skills/temper/SKILL.md (or your agent's skills folder).
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

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

Remove Premature Abstraction

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

Simplify Configuration

text
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

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

© sharpdeveye, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in source/skills/temper of sharpdeveye/maestro.

Open the folder on GitHubat commit 00f9115

Compare with similar skills

Temper next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Temper compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Temper this skillsharpdeveye/maestro592—~649Automated safety check: PassMIT
Generative Engine Optimizationtech-leads-club/agent-skills7k—~2.5kAutomated safety check: PassMIT
Prompt Optimizeraffaan-m/ECC275k2 repos~2.4kAutomated safety check: PassMIT
Prompt Optimizeraffaan-m/ECC275k5 repos~3.8kAutomated safety check: PassMIT
SQL Optimizationgithub/awesome-copilot40k2 repos~2.3kAutomated safety check: PassMIT
Generative Engine Optimizationkostja94/marketing-skills1k—~2.9kAutomated safety check: PassMIT

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All 25 skills in this repo

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  • Compose

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  • Diagnose

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  • Extract Pattern

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  • Fortify

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Questions about Temper

What does Temper do?

A skill your agent uses when the workflow feels over-engineered, has premature optimizations, unnecessary abstraction layers, or complexity beyond actual requirements. Temper is an agent skill from sharpdeveye/maestro. Use when the workflow feels over-engineered, has premature optimizations, unnecessary abstraction layers, or complexity beyond actual requirements.

When should I use Temper?

Temper fits situations like: the workflow feels over-engineered; has premature optimizations; unnecessary abstraction layers; complexity beyond actual requirements.

How do I install Temper in Claude Code?

Run `npx skills add sharpdeveye/maestro --skill temper -a claude-code`. Or copy the skill folder (source/skills/temper in sharpdeveye/maestro) into .claude/skills/temper in your project. Claude Code loads it when a task matches its description.

How do I install Temper in Codex?

Run `npx skills add sharpdeveye/maestro --skill temper -a codex`. Or copy the skill folder (source/skills/temper in sharpdeveye/maestro) into .agents/skills/temper in your project. Codex loads it when a task matches its description.

Can I use Temper in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add sharpdeveye/maestro --skill temper -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/temper, .gemini/skills/temper, .github/skills/temper and .opencode/skills/temper in your project.

What does Temper need to run?

SKILL.md names no scripts, command-line tools or credentials: Temper is instructions for the agent only.

Does Temper access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Temper safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Temper use?

Temper is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Temper use?

About 649 tokens (SKILL.md is roughly 2.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Temper?

Skills that share tags, products or a category with Temper: Generative Engine Optimization (tech-leads-club/agent-skills, 7k stars), Prompt Optimizer (affaan-m/ECC, 275k stars), Prompt Optimizer (affaan-m/ECC, 275k stars) and SQL Optimization (github/awesome-copilot, 40k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Temper?

sharpdeveye (a GitHub user) maintains it in sharpdeveye/maestro, which has 592 GitHub stars. The repository holds 25 skills in this directory. The repository was last updated on April 29, 2026.

Source: sharpdeveye/maestro on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.