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Hiring Scorecard

Organization
nightly-labs
Hiring Scorecard

Build a role-based interview scorecard with consistent questions and evidence-backed evaluation criteria.

Overview

Publishernightly-labs
Repositoryopenbot
Skill nameHiring Scorecard
Stars
521
Forks
81
Bundled files
Instructions only
Links
Skill sourceRepositoryHomepage
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by nightly-labs on GitHub. Read the source before you install it.

Installation

Install the Hiring Scorecard AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/nightly-labs/openbot/tree/main/marketplace/production-catalog/skills/hiring-scorecard
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/nightly-labs/openbot.git /tmp/openbot
mkdir -p .claude/skills
cp -r /tmp/openbot/marketplace/production-catalog/skills/hiring-scorecard .claude/skills/nightly-labs-hiring-scorecard
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Hiring Scorecard in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Hiring Scorecard on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Hiring Scorecard is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Hiring Scorecard

Inputs

Use the role requirements, level, actual work examples, and interview stage. Keep the evaluation tied to job-relevant capabilities.

Workflow

  1. Translate requirements into observable behaviors. Define what weak, adequate, and strong evidence would look like for each criterion.
  2. Write structured questions and work-sample prompts that produce comparable evidence. Avoid personal characteristics unrelated to the role.
  3. For interview notes, separate observed evidence from an interviewer impression. Mark missing evidence instead of guessing ability or motivation.
  4. Summarize strengths, gaps, and follow-up questions. Leave the hiring decision to the responsible people and do not rank candidates from unsupported proxies.

Deliverable

Return a scorecard, interview questions, scoring anchors, and an evidence summary template. Do not contact candidates or change hiring records unless asked.

Frequently asked questions

What does the Hiring Scorecard AI skill do?

Build a role-based interview scorecard with consistent questions and evidence-backed evaluation criteria.

Why use Hiring Scorecard on TypingMind?

Because you install it once and use it with any model. Hiring Scorecard is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Hiring Scorecard in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/nightly-labs/openbot/tree/main/marketplace/production-catalog/skills/hiring-scorecard. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Hiring Scorecard?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Hiring Scorecard?

As many as you like. As long as a model supports skills, you can use Hiring Scorecard with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Hiring Scorecard AI skill free?

It is published on GitHub by nightly-labs. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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