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Evaluating Candidates

Checked
refoundai·vlatest·other·MIT

This skill assesses candidate responses based on predefined criteria, streamlining the hiring process and ensuring consistent evaluations.

Repository

Install on your platform

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

Installs under a different name. Its SKILL.md names it interviewing-evaluating-candidates, not the name it is listed under, so the command below uses that name.
  1. 1

    Run this in your project

    terminal
    $ npx skills add refoundai/lenny-skills --skill interviewing-evaluating-candidates -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

refoundai

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 refoundai/lenny-skills at 13598cc54e.

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

Commit
13598cc54e
Manifest
skills/interviewing-evaluating-candidates/SKILL.md
Scanned
3 files, 2,340 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

The evaluating-candidates skill enables AI agents to assess job candidates based on their resumes, cover letters, and interview responses. It evaluates qualifications, cultural fit, and alignment with company values using predefined criteria.

When to use it

  • Reviewing a large volume of candidate applications efficiently
  • Identifying top candidates for further interviews
  • Ensuring hiring decisions align with organizational goals
  • Automating initial screening processes in recruitment

Key capabilities

  • Resume parsing and analysis
  • Language and tone evaluation
  • Skill and experience matching
  • Cultural fit assessment

Example prompts

  • "Evaluate this candidate's resume against the job description."
  • "Assess whether this applicant is a good cultural fit for our team."
  • "Compare two candidates based on their interview responses."

Tips & gotchas

  • Ensure resumes and cover letters are in clear, structured formats for accurate parsing.
  • Use alongside human judgment to avoid biases or oversights in automated evaluations.