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Prompting

Checked
diskd-ai·vlatest·ai-ml

Generates optimized prompts for diskd-ai models, maximizing output quality and relevance based on user input.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add diskd-ai/prompting --skill prompting -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

diskd-ai

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

No human has reviewed this code. The checks below are a static scan of the files at one commit — nobody has run this skill or judged whether it works. A skill runs with whatever access you give your agent, so read the source before you install it.

Automated safety checks

scanned

This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.

  • Declares what it does: passed

    SKILL.md parses and declares a name and a description.

    SKILL.md exists, its frontmatter parses, and it declares a name and a description.

  • No undeclared network calls: passed

    Makes no network calls.

    Every host the skill dials — from its scripts, its config endpoints or the commands it tells the agent to run — is either well-known package and API infrastructure or declared in its own frontmatter. Links in documentation are not counted.

  • No obfuscated payloads: passed

    No encoded or obfuscated payloads.

    No base64, hex or compressed blob is decoded and then executed, and no encoded shell commands.

  • No credential access: passed

    Reads no keys, tokens, keychains or credential files.

    Neither the code nor the SKILL.md instructions read SSH keys, cloud credentials, keychains, token stores, browser cookie databases or dotfiles that hold secrets.

  • No pipe-to-shell installers: passed

    No pipe-to-shell or download-and-run installers.

    No `curl … | sh` pattern, in the code or in the instructions, that runs code fetched at run time.

  • Pinned to a commit: passed

    Scanned diskd-ai/prompting at 3c2ba8c90e.

    The exact upstream commit SHA that was scanned is recorded, so the result refers to specific bytes.

Commit
3c2ba8c90e
Manifest
SKILL.md
Scanned
5 files, 801 lines
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

What it does

This skill assists users in crafting effective prompts for large language models like Claude, GPT, Gemini, and Llama. It provides a structured workflow and templates to guide prompt creation, focusing on clarity, specificity, and desired output formats. The goal is to maximize the quality and relevance of responses from these AI models by optimizing the input prompts.

When to use it

  • When you need to generate summaries or analyses from text content.
  • For code review tasks requiring specific security, performance, or maintainability checks.
  • When you want to enforce a particular output format like Markdown, JSON, or XML.
  • To improve the consistency and accuracy of responses from AI models.
  • When dealing with complex reasoning or multi-step workflows that benefit from techniques like chain-of-thought prompting.

Key capabilities

  • Prompt Templates: Provides structured templates for prompt creation including optional context/role, required task definition, constraints, output format, and examples.
  • Technique Guidance: Offers a quick reference to prompting techniques such as few-shot learning, chain-of-thought reasoning, role prompting, task decomposition, and constraint specification.
  • Output Format Specification: Supports defining desired output formats including XML, JSON, and Markdown.
  • Troubleshooting Guide: Includes a guide for diagnosing common prompt issues (vague outputs, wrong format, missing details, inconsistent results, off-topic responses) with suggested solutions.
  • Improvement Checklist: Provides a checklist to evaluate the effectiveness of existing prompts.

Example prompts

  • "Summarize this article in 3 bullet points." (Minimal Prompt)
  • "You are a senior code reviewer. Review this code for: Security vulnerabilities, Performance issues, Maintainability concerns. Format your response as: ## Summary [1-2 sentences] ## Issues - [severity]: [description] ## Recommendations [prioritized list]" (Structured Prompt)

Tips & gotchas

  • Specificity is key: Replace vague instructions like "be concise" with concrete limits like "under 100 words."
  • Format matters: Explicitly define the desired output format to ensure consistency and usability.
  • Explore techniques: Refer to references/techniques.md for detailed patterns and examples of prompting techniques.