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Requirement Analyzer

Checked
masanao-ohba·vlatest·other

This Requirement Analyzer dissects textual requirements to identify key elements and potential ambiguities, streamlining analysis & ensuring clarity.

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 masanao-ohba/claude-manifests --skill requirement-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

masanao-ohba

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 masanao-ohba/claude-manifests at 3e765ad5ee.

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

Commit
3e765ad5ee
Manifest
skills/generic/requirement-analyzer/SKILL.md
Scanned
2 files, 754 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

What it does

The requirement-analyzer skill helps extract and organize requirements from text. It can identify key features, constraints, and dependencies described within a document or conversation. This allows for more structured understanding of complex needs and facilitates planning and execution.

When to use it

  • Analyzing user stories to break down project scope.
  • Processing meeting transcripts to create actionable tasks.
  • Reviewing technical specifications to identify potential risks or gaps.
  • Extracting requirements from legal documents or contracts.

Key capabilities

  • Requirement extraction
  • Organization of extracted information
  • Identification of key features and constraints

Example prompts

  • "Analyze this user story and list the key requirements."
  • "From this meeting transcript, extract all action items and their associated deadlines."
  • "Can you identify any dependencies or potential risks from these technical specifications?"

Tips & gotchas

The quality of extracted requirements depends heavily on the clarity and structure of the input text. Complex or ambiguous language may require refinement of prompts for optimal results.