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Agent skill

Interviewing Evaluating Candidates

by RefoundAI in RefoundAI/lenny-skills

Help users design and execute a high-signal interview process that prioritizes real-world performance over superficial charisma or pedigree.

MITAuto-check passed

Install Interviewing Evaluating Candidates

skills CLI
$ npx skills add RefoundAI/lenny-skills --skill interviewing-evaluating-candidates -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install RefoundAI/lenny-skills interviewing-evaluating-candidates --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/RefoundAI/lenny-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/interviewing-evaluating-candidates .claude/skills/interviewing-evaluating-candidates && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
interviewing-evaluating-candidates
GitHub stars
1.4k
Token cost
~1.3k tokens
SKILL.md length
727 words
Files
3 (incl. references)
Skills in repo
76
Repo updated
First seen
Licence
MIT

At a glance

Help users design and execute a high-signal interview process that prioritizes real-world performance over superficial charisma or pedigree.

  • Works in 4 steps: Define the Role Core - Identify specific… → Design Practical Assessments - Move from… → Apply Standardized Evaluation -… → …
  • SKILL.md covers How to Help, Core Principles, Questions to Help Users and Common Mistakes to Flag, plus 2 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Interviewing Evaluating Candidates is an agent skill from RefoundAI/lenny-skills. Help users design and execute a high-signal interview process that prioritizes real-world performance over superficial charisma or pedigree.

Its SKILL.md is about 1.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files, including reference files (for example `references/artifacts.md` and `references/guest-insights.md`).

The repository describes itself as: 86 product management skills from Lenny's Podcast for Claude Code and AI agents. Hiring, user research, strategy, shipping, and more. The licence is MIT.

Example prompts

  • “/interviewing-evaluating-candidates”

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

  1. Define the Role Core - Identify specific competencies and core jobs the candidate must perform based on your unique organizational needs.
  2. Design Practical Assessments - Move from abstract case studies to almost-real-life assignments or paid work trials that mimic the actual…
  3. Apply Standardized Evaluation - Implement consistent rubrics and thematic questioning to reduce bias and increase signal quality.
  4. Conduct High-Fidelity Reference Checks - Verify performance with past collaborators to triangulate interview signals and uncover long-term…

What it can do on your machine

Read from SKILL.md and the folder at commit 13598cc. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Interviewing Evaluating Candidates loads about 1.3k tokens when it runs, and up to ~40k if it reads all its reference files. Until then it costs about 44 tokens; SKILL.md has 727 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~44
When it runs · the whole SKILL.md, loaded when a task matches
~1.3k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~40k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from RefoundAI/lenny-skills at commit 13598cc, republished under its MIT licence (© RefoundAI). 727 words, ~1,263 tokens.

Download SKILL.mdSave it as .claude/skills/interviewing-evaluating-candidates/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
interviewing-evaluating-candidates
description
Help users design and execute a high-signal interview process that prioritizes real-world performance over superficial charisma or pedigree.

Interviewing and Evaluating Candidates

Move beyond resumes to assess high-fidelity signals like agency, first-principles thinking, and actual craft.

Help the user with interviewing and evaluating candidates using insights from 27 guests and posts across Lenny's Podcast and Newsletter.

How to Help

  1. Define the Role Core - Identify specific competencies and core jobs the candidate must perform based on your unique organizational needs.
  2. Design Practical Assessments - Move from abstract case studies to almost-real-life assignments or paid work trials that mimic the actual job.
  3. Apply Standardized Evaluation - Implement consistent rubrics and thematic questioning to reduce bias and increase signal quality.
  4. Conduct High-Fidelity Reference Checks - Verify performance with past collaborators to triangulate interview signals and uncover long-term patterns.

Core Principles

Prioritize Enthusiastic Rehires

Brian Halligan: "I think CEOs and everyone dramatically overrates their ability to interview, and overrates their gut feeling, and underrates a really high quality blind reference."

The most effective hiring signal is asking a reference if the candidate was in the top 1 percent of employees and if they would enthusiastically rehire them.

Use the Unsell Email

Kevin Yien: "When you get to offer stage, I send an email and I say all the terrible things that are probably going to reinforce their fears. If you can tell them that upfront and they can read that whole email and still be equally excited to join you, find yourself a A+ hire."

Send an email at the offer stage detailing your company's biggest flaws and challenges to ensure the candidate's commitment is based on reality.

Screen for First-Principles Thinking

Melissa Tan: "I think they looked for two main things. They looked for first principles thinkers, so not necessarily your experience, but how do you approach problems, how do you know the right questions to ask? And then create your own framework around that. Dropbox also hired for people that were just really humble, collaborative and team oriented."

Evaluate how candidates create their own frameworks rather than relying on experience to find those capable of driving cross-functional innovation.

Hire Future Strategy Drivers

Peter Deng: "In 6 months, if I'm telling you what to do, I've hired the wrong person. It helps me and the person operate on a different level where the goal is not, did you hit this OKR? The Meta goal becomes, are we calibrating enough? Are we actually getting into a spot where in 6 months you're the one telling me what needs to be done?"

Focus on finding individuals who will eventually drive the strategy and direct their managers within six months of starting.

Show full SKILL.md (298 more words)Show less
Stack Rank References First

Shishir Mehrotra: "I generally value the reference check over interview signals. If I had to stack rank in interviews, what is the best signal? The reference check is the top of the list. Those people, they worked with this person sometimes for years, their knowledge, what you're going to get out of 30 minutes of artificial scenarios it's just like never going to compare what a good reference check will give you."

Reference checks offer a high-fidelity signal of long-term performance that artificial interview environments cannot replicate; treat them as your primary signal.

Questions to Help Users

  • "What are the specific jobs or outcomes this hire needs to achieve in their first six months?"
  • "Are you currently using a standardized rubric to evaluate all candidates for this role?"
  • "What real-world problem from your current roadmap could serve as a work trial project?"
  • "How are you screening for cultural traits like humility, agency, or clock speed?"
  • "What is the most common reason candidates fail in this specific role at your company?"
  • "How are you differentiating between a candidate's personal impact versus the success of their previous company?"

Common Mistakes to Flag

  • Over-indexing on interview charisma - Polished interview skills are often poor predictors of actual job performance and technical depth.
  • Hiring for domain experience over first-principles - Relying on established playbooks prevents candidates from solving unique problems in evolving environments.
  • Treating reference checks as a formality - References provide the only longitudinal data on a candidate's behavior and performance over years.
  • Using abstract or hypothetical case studies - Hypotheticals reveal how someone thinks about imaginary problems rather than how they execute on real ones.

Deep Dive

For all 39 sourced insights from 27 guests, see references/guest-insights.md

  • Hiring Product Talent
  • Org Design
  • Building Growth Team
  • Founding Exec Team

© RefoundAI, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 2 other files (references) in skills/interviewing-evaluating-candidates of RefoundAI/lenny-skills.

  • SKILL.md
  • references/artifacts.md
  • references/guest-insights.md

Open the folder on GitHubat commit 13598cc

Compare with similar skills

Interviewing Evaluating Candidates next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Interviewing Evaluating Candidates compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Interviewing Evaluating Candidates this skillRefoundAI/lenny-skills1.4k—~1.3kAutomated safety check: PassMIT
Interviewalirezarezvani/claude-skills28k—~1.1kAutomated safety check: PassMIT
Executealirezarezvani/claude-skills28k—~831Automated safety check: PassMIT
Arize Evaluatorgithub/awesome-copilot40k1 repos~8.1kAutomated safety check: NotesMIT
SignalsPostHog/posthog40k—~4.3kAutomated safety check: PassCustom licence
Interviewcodewhale-hq/Codewhale41k—~232Automated safety check: PassMIT

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Questions about Interviewing Evaluating Candidates

What does Interviewing Evaluating Candidates do?

Help users design and execute a high-signal interview process that prioritizes real-world performance over superficial charisma or pedigree. Interviewing Evaluating Candidates is an agent skill from RefoundAI/lenny-skills. Help users design and execute a high-signal interview process that prioritizes real-world performance over superficial charisma or pedigree.

How do I install Interviewing Evaluating Candidates in Claude Code?

Run `npx skills add RefoundAI/lenny-skills --skill interviewing-evaluating-candidates -a claude-code`. Or copy the skill folder (skills/interviewing-evaluating-candidates in RefoundAI/lenny-skills) into .claude/skills/interviewing-evaluating-candidates in your project. Claude Code loads it when a task matches its description.

How do I install Interviewing Evaluating Candidates in Codex?

Run `npx skills add RefoundAI/lenny-skills --skill interviewing-evaluating-candidates -a codex`. Or copy the skill folder (skills/interviewing-evaluating-candidates in RefoundAI/lenny-skills) into .agents/skills/interviewing-evaluating-candidates in your project. Codex loads it when a task matches its description.

Can I use Interviewing Evaluating Candidates in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add RefoundAI/lenny-skills --skill interviewing-evaluating-candidates -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/interviewing-evaluating-candidates, .gemini/skills/interviewing-evaluating-candidates, .github/skills/interviewing-evaluating-candidates and .opencode/skills/interviewing-evaluating-candidates in your project.

What does Interviewing Evaluating Candidates need to run?

SKILL.md names no scripts, command-line tools or credentials: Interviewing Evaluating Candidates is instructions for the agent only.

Does Interviewing Evaluating Candidates access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Interviewing Evaluating Candidates safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Interviewing Evaluating Candidates use?

Interviewing Evaluating Candidates is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Interviewing Evaluating Candidates use?

About 1.3k tokens (SKILL.md is roughly 5.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 39k tokens, read only when the agent opens those files.

What are the alternatives to Interviewing Evaluating Candidates?

Skills that share tags, products or a category with Interviewing Evaluating Candidates: Interview (alirezarezvani/claude-skills, 28k stars), Execute (alirezarezvani/claude-skills, 28k stars), Arize Evaluator (github/awesome-copilot, 40k stars) and Signals (PostHog/posthog, 40k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Interviewing Evaluating Candidates?

RefoundAI (a GitHub organization) maintains it in RefoundAI/lenny-skills, which has 1,381 GitHub stars. The repository holds 76 skills in this directory. The repository was last updated on July 16, 2026.

Source: RefoundAI/lenny-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.