interview-system-designer
This skill should be used when the user asks to "design interview processes", "create hiring pipelines", "calibrate interview loops", "generate interview questions", "design competency matrices", "analyze interviewer bias", "create scoring rubrics", "build question banks", or "optimize hiring systems". Use for designing role-specific interview loops, competency assessments, and hiring calibration systems.
Best use case
interview-system-designer is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
This skill should be used when the user asks to "design interview processes", "create hiring pipelines", "calibrate interview loops", "generate interview questions", "design competency matrices", "analyze interviewer bias", "create scoring rubrics", "build question banks", or "optimize hiring systems". Use for designing role-specific interview loops, competency assessments, and hiring calibration systems.
Teams using interview-system-designer should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/interview-system-designer/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How interview-system-designer Compares
| Feature / Agent | interview-system-designer | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
This skill should be used when the user asks to "design interview processes", "create hiring pipelines", "calibrate interview loops", "generate interview questions", "design competency matrices", "analyze interviewer bias", "create scoring rubrics", "build question banks", or "optimize hiring systems". Use for designing role-specific interview loops, competency assessments, and hiring calibration systems.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# Interview System Designer Comprehensive interview loop planning and calibration support for role-based hiring systems. ## Overview Use this skill to create structured interview loops, standardize question quality, and keep hiring signal consistent across interviewers. ## Core Capabilities - Interview loop planning by role and level - Round-by-round focus and timing recommendations - Suggested question sets by round type - Framework support for scoring and calibration - Bias-reduction and process consistency guidance ## Quick Start ```bash # Generate a loop plan for a role and level python3 scripts/interview_planner.py --role "Senior Software Engineer" --level senior # JSON output for integration with internal tooling python3 scripts/interview_planner.py --role "Product Manager" --level mid --json ``` ## Recommended Workflow 1. Run `scripts/interview_planner.py` to generate a baseline loop. 2. Align rounds to role-specific competencies. 3. Validate scoring rubric consistency with interview panel leads. 4. Review for bias controls before rollout. 5. Recalibrate quarterly using hiring outcome data. ## References - `references/interview-frameworks.md` - `references/bias_mitigation_checklist.md` - `references/competency_matrix_templates.md` - `references/debrief_facilitation_guide.md` ## Common Pitfalls - Overweighting one round while ignoring other competency signals - Using unstructured interviews without standardized scoring - Skipping calibration sessions for interviewers - Changing hiring bar without documenting rationale ## Best Practices 1. Keep round objectives explicit and non-overlapping. 2. Require evidence for each score recommendation. 3. Use the same baseline rubric across comparable roles. 4. Revisit loop design based on quality-of-hire outcomes.
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