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Prompt Analyzer

Checked
huangserva·vlatest·ai-ml

Analyzes prompts to identify key elements & potential issues, boosting prompt effectiveness and improving AI response quality.

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 huangserva/skill-prompt-generator --skill prompt-analyzer -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

huangserva

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 huangserva/skill-prompt-generator at e951249840.

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

Commit
e951249840
Manifest
.codex/skills/prompt-analyzer/SKILL.md
Scanned
2 files, 1,106 lines
Copies in repo
2 — all of them scanned
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

The prompt-analyzer skill evaluates user inputs to identify potential issues, ambiguities, or missing context before an AI agent executes a task. It acts as a pre-flight check to ensure instructions are clear and actionable, reducing the likelihood of errors in complex workflows.

When to use it

  • Before submitting complex multi-step coding tasks to verify logic flow and variable definitions.
  • When drafting creative writing prompts to check for specific tone, style, or constraint requirements.
  • During data analysis requests to ensure the query includes necessary context about the dataset structure.
  • Prior to deploying automated agent workflows to validate that trigger conditions are explicitly defined.

Key capabilities

  • Identifies ambiguous phrasing or vague instructions within a prompt.
  • Highlights missing critical information required for successful task execution.
  • Assesses potential conflicts between different constraints in the same request.
  • Provides feedback on prompt structure to improve clarity and effectiveness.

Example prompts

  • "Analyze this prompt for any ambiguities: 'Write a summary of the article.'"
  • "Review my coding instruction to see if I've defined all necessary variables and libraries."
  • "Check if my data analysis request includes enough context about the source dataset."

Tips & gotchas

Ensure you provide the full intended prompt for analysis, as partial inputs may lead to incomplete feedback. While this skill improves prompt quality, it does not execute the task itself; it only prepares the instruction for execution.