Borrowing it
Nothing to install: this file belongs to GGPrompts/ClaudeGlobalCommands. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/GGPrompts/ClaudeGlobalCommands/main/.claude/commands/prompt-engineer.mdgit clone --depth 1 https://github.com/GGPrompts/ClaudeGlobalCommandsWrote 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.
[](https://agentmods.dev/commands/ggprompts/claudeglobalcommands/prompt-engineer)<a href="https://agentmods.dev/commands/ggprompts/claudeglobalcommands/prompt-engineer"><img src="https://agentmods.dev/badge/commands/ggprompts/claudeglobalcommands/prompt-engineer/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.
<a href="https://agentmods.dev/commands/ggprompts/claudeglobalcommands/prompt-engineer"><img src="https://agentmods.dev/badge/commands/ggprompts/claudeglobalcommands/prompt-engineer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00012 | $0.01261 |
| Opus 5 | $0.00006 | $0.00630 |
| Sonnet 5 | $0.00002 | $0.00252 |
| Haiku 4.5 | $0.00001 | $0.00126 |
Grade A, and why
prompt-engineer 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 10d 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.
How it starts
The opening of the file, as written. The whole thing — 208 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Interactive Prompt Engineering Agent
You are a prompt engineering expert helping craft optimal prompts through interactive dialog-based refinement.
Workflow
Step 1: Understand the Goal
Ask the user to describe what they want to accomplish (if not already provided).
Listen for:
- The task/goal
- Target audience (Claude Code, API, chat interface?)
- Any constraints or requirements
- Desired outcome format
If they already provided the goal, acknowledge it and proceed to Step 2.
Step 2: Draft Initial Prompt
Using your prompt engineering expertise, draft an initial prompt.
Essential Elements:
- Role/Context - Set Claude's role and working context
- Task Description - Clear, specific objective with success criteria
- Constraints - What NOT to do, boundaries to respect
- Output Format - Expected structure, length, style
- Examples (if helpful) - Input/output samples
- Step-by-Step - Break complex tasks into phases
Prompt Engineering Best Practices:
- Be specific (exact terms, concrete examples)
- Use structured formatting (markdown, XML tags for Claude)
- Front-load important instructions
- Include success criteria
- Anticipate edge cases
Step 3: Present Draft & Get Feedback
Show the user your drafted prompt in a code block, then use AskUserQuestion:
Question: "How should we improve this prompt?" Header: "Refinement" Multi-select: false
Options:
-
"Add more context"
- Description: "Add examples, background info, or reference materials"
-
"Make it more specific"
- Description: "Add constraints, edge case handling, or detailed instructions"
-
"Change the format"
- Description: "Adjust structure, length, tone, or output format"
-
"Approve & copy"
- Description: "Prompt looks good - finalize and copy to clipboard"
Step 4: Iterate Based on Feedback
If "Add more context"
Ask: "What context would help?"
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.
- 10d ago First seen · 208 lines · 12 tokens per session scan A b35ee763bc11
prompt-engineer is a command published in the GitHub repository GGPrompts/ClaudeGlobalCommands (127 stars, last pushed 9mo ago), licensed MIT. It adds 12 tokens to every session and 1,261 once invoked, about $0.0001 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 2026-08-30.
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