prompt-engineering

prompt-engineering is a skill for Claude Code from VersoXBT/claude-initial-setup. It costs 60 tokens per session (1,704 once invoked), scanned A, original, MIT.

A guide to writing instructions for Claude, Anthropic’s AI models, so their replies follow a desired format or approach.

In plain words
What is it for?
Use it to design system prompts, add example inputs and outputs, request structured JSON, create reusable prompt templates, or improve Claude responses.
Why use it?
It helps make prompts clearer and more repeatable when you need reliable answers, structured data, or a consistent role and set of rules.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the claude-initial-setup plugin — 75 skills, 15 commands, 14 agents, 2 hooks shipped together

Good fit Use it to design system prompts, add example inputs and outputs, request structured JSON, create reusable prompt templates, or improve Claude responses.

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Install with agentmods
npx agentmods add skills/versoxbt/claude-initial-setup/prompt-engineering
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add VersoXBT/claude-initial-setup --skill prompt-engineering
Clone the repo
git clone --depth 1 https://github.com/VersoXBT/claude-initial-setup

Made for: Claude Code.

Or install claude-initial-setup, the plugin that ships this one along with the rest of its 75 skills, 15 commands, 14 agents, 2 hooks.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for prompt-engineering

README.md
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Your own site
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Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for prompt-engineering

Your own site · 80×15
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Per session 60 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,704 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00060 $0.01704
Opus 5.5 $0.00024 $0.00682
Sonnet 5.5 $0.00012 $0.00341
Haiku 4.5 $0.00006 $0.00170

Measured 1mo ago against content hash 8d4553b0e801, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

prompt-engineering scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/claude-api/prompt-engineering/SKILL.md · 214 lines

How it starts

The opening of the file, as written. The whole thing — 214 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Prompt Engineering

Patterns and techniques for crafting effective Claude prompts. Covers system prompts, few-shot learning, chain-of-thought reasoning, structured output, and prefilling.

When to Use

  • User is writing or optimizing prompts for Claude
  • User needs structured JSON output from Claude
  • User is designing system prompts or instructions
  • User wants chain-of-thought reasoning or few-shot examples
  • User is building prompt templates for reuse

Core Patterns

System Prompts

System prompts set Claude's persona, constraints, and output format. Place stable instructions here; they are cached separately and can use prompt caching.

message = client.messages.create(
    model="claude-sonnet-4-6-20250514",
    max_tokens=1024,
    system="""You are a senior code reviewer. Follow these rules:
1. Focus on bugs, security issues, and performance problems.
2. Rate severity as CRITICAL, HIGH, MEDIUM, or LOW.
3. Provide a fix for each issue found.
4. If the code is clean, say "No issues found." and nothing else.""",
    messages=[{"role": "user", "content": f"Review this code:\n```\n{code}\n```"}]
)

Few-Shot Examples

Provide 2-4 input/output examples to demonstrate the exact format and reasoning you expect. Use the messages array with alternating user/assistant turns.

messages = [
    {"role": "user", "content": "Classify: 'My order never arrived and nobody responds to emails'"},
    {"role": "assistant", "content": '{"category": "shipping", "sentiment": "negative", "priority": "high"}'},
    {"role": "user", "content": "Classify: 'Love the new feature update, works great!'"},
    {"role": "assistant", "content": '{"category": "feedback", "sentiment": "positive", "priority": "low"}'},
    {"role": "user", "content": f"Classify: '{user_input}'"}
]

message = client.messages.create(
    model="claude-sonnet-4-6-20250514",
    max_tokens=256,
    messages=messages
)

Chain-of-Thought Reasoning

Ask Claude to reason step-by-step before giving a final answer. Use extended thinking for complex problems that benefit from deep reasoning.

Read the full file on GitHub · 214 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 1mo ago First seen · 214 lines · 60 tokens per session scan A 8d4553b0e801

Subscribe to this mod's changes

prompt-engineering is a skill published in the GitHub repository VersoXBT/claude-initial-setup (4 stars, last pushed 5mo ago), licensed MIT. It adds 60 tokens to every session and 1,704 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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