prompt-engineering

prompt-engineering is a skill for Claude Code from bhaumikmaan/claude-code-master-skills. It costs 61 tokens per session (1,537 once invoked), scanned A, original, MIT.

A guided method for turning a repeatable workflow into a reusable coding-agent skill or agent setup. It uses structured questions and templates to define the steps, inputs, tools, and expected output.

In plain words
What is it for?
Use it to create SKILL.md files, design agent personas, define structured output formats, or turn an informal process into a repeatable workflow.
Why use it?
It helps capture how a task should be done without forgetting important decisions or inventing rules that conflict with the project. The result can be reused for similar requests.

Skill for Claude Code

Written for Claude Code: disable-model-invocation in frontmatter. Also seen: reads .claude/ paths; mentions CLAUDE.md; mentions subagents.

Good fit Use it to create SKILL.md files, design agent personas, define structured output formats, or turn an informal process into a repeatable workflow.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/bhaumikmaan/claude-code-master-skills/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 bhaumikmaan/claude-code-master-skills --skill prompt-engineering
Clone the repo
git clone --depth 1 https://github.com/bhaumikmaan/claude-code-master-skills

Made for: Claude Code.

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
[![agentmods](https://agentmods.dev/badge/skills/bhaumikmaan/claude-code-master-skills/prompt-engineering/github.svg)](https://agentmods.dev/skills/bhaumikmaan/claude-code-master-skills/prompt-engineering)
Your own site
<a href="https://agentmods.dev/skills/bhaumikmaan/claude-code-master-skills/prompt-engineering"><img src="https://agentmods.dev/badge/skills/bhaumikmaan/claude-code-master-skills/prompt-engineering/github.svg" alt="Measured on agentmods" height="20"></a>

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
<a href="https://agentmods.dev/skills/bhaumikmaan/claude-code-master-skills/prompt-engineering"><img src="https://agentmods.dev/badge/skills/bhaumikmaan/claude-code-master-skills/prompt-engineering.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 61 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,537 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 $0.00061 $0.01537
Opus 5 $0.00030 $0.00768
Sonnet 5 $0.00012 $0.00307
Haiku 4.5 $0.00006 $0.00154

Measured 12d ago against content hash ca136fb11c67, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, 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 12d 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/prompt-engineering/SKILL.md · 176 lines

How it starts

The opening of the file, as written. The whole thing — 176 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Prompt Engineering

CRITICAL: Check existing project conventions before inventing new ones. Read CLAUDE.md, .claude/rules/, and existing skills to align with what's already established.

Skill Creation Workflow

Step 1: Analyze the Session/Request

Before asking questions, analyze what you already know:

  • What repeatable process was performed or requested
  • What the inputs/parameters are
  • The distinct steps in order
  • Success criteria for each step
  • Where the user steered or corrected during the session
  • What tools and permissions are needed

Step 2: Interview (4 Rounds)

Use structured questions. Don't over-ask for simple processes.

Round 1 — High-Level Confirmation

  • Suggest a name and description. Ask to confirm or rename.
  • Suggest goal(s) and specific success criteria.

Round 2 — Details

  • Present the steps as a numbered list.
  • Suggest arguments based on observed inputs.
  • Ask: inline (current conversation) or forked (sub-agent with own context)?
    • Fork for self-contained tasks without mid-process user input
    • Inline when the user wants to steer mid-process
  • Ask where to save:
    • This repo (.claude/skills/<name>/SKILL.md) — project-specific workflows
    • Personal (~/.claude/skills/<name>/SKILL.md) — follows you across repos

Round 3 — Per-Step Breakdown For each major step, if not obvious:

  • What does this step produce that later steps need?
  • What proves this step succeeded?
  • Should the user confirm before proceeding? (especially irreversible actions)
  • Are any steps independent and could run in parallel?
  • What are the hard constraints?

Round 4 — Final

  • Confirm when the skill should be invoked. Suggest trigger phrases.
  • Ask for gotchas or edge cases.

Step 3: Write the SKILL.md

Use this template:

---
name: {{skill-name}}
description: {{one-line description}}
allowed-tools:
  {{list of tool permission patterns}}
when_to_use: {{detailed invocation triggers with example phrases}}
argument-hint: "{{hint showing argument placeholders}}"
arguments:
  {{list of argument names}}
context: {{inline or fork — omit for inline}}
---

# {{Skill Title}}
Description of skill

## Inputs
- `$arg_name`: Description of this input

## Goal
Clearly stated goal with defined artifacts or completion criteria.

## Steps

### 1. Step Name
What to do. Be specific and actionable. Include commands when appropriate.

**Success criteria**: What proves this step is done.

Read the full file on GitHub · 176 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 12d ago First seen · 176 lines · 61 tokens per session scan A ca136fb11c67

Subscribe to this mod's changes

prompt-engineering is a skill published in the GitHub repository bhaumikmaan/claude-code-master-skills (3 stars, last pushed 5mo ago), licensed MIT. It adds 61 tokens to every session and 1,537 once invoked, about $0.0003 per session on Opus 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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