Hiring rubric
Skill The-AI-Directory-Company/agents-and-skills/skills/hiring-rubric
Build structured hiring rubrics — defining evaluation dimensions, behavioral interview questions, scoring criteria, and calibration processes that maximize signal and minimize bias.From its SKILL.md
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SKILL.md
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Hiring Rubric
Before you start
Gather the following from the user:
- What role are you hiring for? (Title, level, team)
- What does success look like at 6 months? (3-5 concrete outcomes the hire should achieve)
- What are the must-have vs nice-to-have skills? (Technical and non-technical)
- How many interview rounds? (Phone screen, technical, system design, behavioral, culture)
- Who is on the interview panel? (Names and which dimensions they'll evaluate)
If the user says "we need a strong engineer," push back: "Strong at what? Backend systems? Cross-team collaboration? Debugging production issues? Define 3-4 specific capabilities that matter most for this role."
Hiring rubric template
1. Role Profile
Write a concise profile that anchors the rubric to actual job needs, not a generic job description. Include: role title, team, level, reporting line, and 2-3 concrete 6-month goals the hire should achieve.
2. Evaluation Dimensions
Define 4-6 dimensions. Each dimension must be independent — avoid overlap. Assign a weight reflecting its importance to the role.
| Dimension | Weight | Assessed In |
|------------------------|--------|----------------------|
| Technical depth | 30% | Technical interview |
| System design | 25% | Design interview |
| Problem-solving | 20% | Technical interview |
| Communication | 15% | All rounds |
| Collaboration | 10% | Behavioral interview |
3. Scoring Criteria
For each dimension, define what a 1 through 4 looks like. Avoid vague language — describe observable behaviors.
Dimension: Technical Depth
4 - Strong Hire: Solves the problem correctly with clean, production-quality
code. Identifies edge cases proactively. Discusses tradeoffs
of their approach without prompting.
3 - Hire: Solves the problem with minor issues. Handles most edge
cases when prompted. Can articulate why they chose their
approach.
2 - Weak: Reaches a partial solution with significant guidance.
Misses important edge cases. Struggles to compare
alternative approaches.
1 - No Hire: Cannot make meaningful progress on the problem. Shows
gaps in fundamentals expected at this level.
Write a scoring rubric like this for every dimension. Use concrete behaviors, not personality traits.
4. Interview Questions
For each dimension, provide 2-3 questions with follow-ups. Behavioral questions must use the "Tell me about a time..." format to elicit past behavior, not hypotheticals.
For technical dimensions, use role-specific coding or debugging problems with follow-ups like "How would you test this in production?" For behavioral dimensions, use "Tell me about a time..." questions that elicit past behavior with follow-ups exploring outcomes and lessons learned.
5. Scorecard
Create a standardized scorecard every interviewer fills out within 24 hours of the interview.
Candidate: _______________ Interviewer: _______________
Role: _______________ Date: _______________
Round: _______________
| Dimension | Score (1-4) | Evidence (required) |
|------------------------|-------------|-------------------------------|
| Technical depth | | |
| System design | | |
| Problem-solving | | |
| Communication | | |
| Collaboration | | |
Overall recommendation: [ ] Strong Hire [ ] Hire [ ] Weak [ ] No Hire
Key strengths:
Key concerns:
The "Evidence" column is mandatory. A score without a specific observation is not valid.
6. Calibration Process
Before interviews begin, have all interviewers score the same mock interview independently, then compare. Align on what a "3" looks like for each dimension with a concrete example. During the process, interviewers submit scorecards before the debrief — the most junior interviewer presents first to prevent anchoring.
Quality checklist
Before using the rubric, verify:
- Every dimension maps to a real job requirement, not a generic trait
- Scoring criteria describe observable behaviors at each level
- No two dimensions overlap significantly (test: could one score high on dimension A and low on dimension B?)
- Behavioral questions ask about past experiences, not hypothetical scenarios
- The scorecard requires written evidence for every score
- Weights total 100% and reflect actual role priorities
- The calibration process is documented and scheduled before interviews begin
- At least one dimension assesses collaboration or communication
Common mistakes to avoid
- Generic dimensions. "Technical skills" is too broad. "Ability to design fault-tolerant distributed systems" is specific enough to evaluate. Tie every dimension to what the person will actually do in the role.
- Hypothetical interview questions. "What would you do if..." invites rehearsed answers. "Tell me about a time when..." surfaces real behavior. Always prefer behavioral questions for non-technical dimensions.
- Missing the evidence requirement. Without mandatory evidence, scorecards become gut-feel ratings. Require interviewers to write the specific moment or statement that justified their score.
- Anchoring in debriefs. If the hiring manager shares their opinion first, everyone adjusts toward it. Always have the most junior interviewer present first, and submit scores before the meeting.
- Overweighting technical skills. A brilliant engineer who can't communicate or collaborate will slow the team down. Ensure at least 20-25% of the weight covers non-technical dimensions.
What ships with it: 4 files
22.4 KB alongside SKILL.md
assets/
- scorecard-template.md3.2 KB
examples/
references/
Gives 0 of the 12 instructions most hr recruiting skills give in ~1.2k tokens
Counted across 356 of the 357 authors here whose files we hold, read 2026-08-07
- Quantify achievements with specific metricsin 14 of 356, across 6 files
- Keep the resume under two pagesin 14 of 356, across 6 files
- Request the full job description if not providedin 12 of 356, across 4 files
- Extract keywords and prioritize job requirementsin 12 of 356, across 4 files
- Stop and ask for clarification if required inputs are missingin 12 of 356, across 5 files
- Map candidate experience to job requirementsin 11 of 356, across 3 files
- Ask if the user wants adjustmentsin 11 of 356, across 3 files
- Provide strengths and gap analysis after the resumein 10 of 356, across 2 files
- Request candidate background details if not providedin 10 of 356, across 2 files
- Format experience bullets as action verb plus resultin 10 of 356, across 2 files
- Ask for missing inputs before startingin 10 of 356, across 9 files
- Use exact job description terminologyin 9 of 356, across 1 file
Said here and by no other author read
- gather role profile from user before starting
- push back on vague role descriptions
- assign a weight to each evaluation dimension
- define independent evaluation dimensions
- describe observable behaviors in scoring criteria
- use behavioral questions for non-technical dimensions
Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.