Setup & Installation
Or with the ClawHub CLI, for registry-managed skill folders outside a full OpenClaw workspace:
What This Skill Does
Analyzes interview transcripts using dynamic expert routing, automatically selecting domain specialists based on role type. Distinguishes genuine candidate capability from rehearsed methodology by focusing on specific past actions and outcomes. Covers product management, engineering, design, operations, sales, and data science roles.
Routes analysis through role-appropriate expert frameworks rather than applying a one-size-fits-all rubric, which surfaces domain-specific red flags that generic evaluation misses.
When to use it
- Comparing candidate stories across multiple interview rounds for consistency
- Flagging vague job titles or exaggerated metrics in a resume
- Evaluating whether an engineer deflected blame or anticipated technical issues
- Reviewing interviewer performance after a debrief session
- Generating structured hiring decision notes from raw transcript files
Example Workflow
Here's how your AI assistant might use this skill in practice.
User asks: Analyze this product manager candidate's three interview transcripts, focusing on product thinking
- 1Identifies role type as Product Manager and selects Marty Cagan and Geoff Smart as the expert combination
- 2Reconstructs candidate's experience timeline across all three rounds and checks for consistency in reasons for leaving and project outcomes
- 3Selects 1-2 core STAR episodes and tests whether candidate applied first principles or recited MECE/SWOT frameworks
- 4Flags attribution fallacies, vague titles, and any solution-bias patterns in the candidate's responses
- 5Generates Profile, Insight, and Structure Note cards saved to people/{candidate_name}/analysis/
Markdown analysis cards covering fact-checked profile, deep product thinking assessment, and a hub document linking all cards for hiring decision closure