Measure and optimize growth using the AARRR (Pirate Metrics) framework with stage-specific KPIs and funnel analysis
日本語の概要は準備中です。原文の説明を表示しています。
Screen resumes efficiently against job requirements with structured scoring, red flag identification, and interview recommendations
日本語の概要は準備中です。原文の説明を表示しています。
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Systematically evaluate resumes against job requirements to identify qualified candidates, flag concerns, and prioritize for interviews.
Based on structured interviewing research and EEOC guidelines, combining:
| Claude Does | You Decide |
|---|---|
| Creates screening rubrics | Hiring decisions |
| Scores against criteria | Culture fit assessment |
| Identifies red/green flags | Interview invitation |
| Summarizes qualifications | Final selection |
| Flags potential concerns | Exception handling |
Required vs. Preferred:
| Category | Must Have | Nice to Have |
|---|---|---|
| Education | Minimum degree | Advanced degree |
| Experience | X years in Y | Specific industry |
| Skills | Core technical | Adjacent skills |
| Certifications | Required licenses | Preferred certs |
Scoring Weight:
| Criterion | Weight | Rationale |
|---|---|---|
| Required experience | 40% | Core capability |
| Required skills | 30% | Day-one impact |
| Education | 15% | Foundation |
| Preferred qualifications | 15% | Growth potential |
Scoring Scale:
| Score | Definition |
|---|---|
| 4 | Exceeds requirement significantly |
| 3 | Meets requirement fully |
| 2 | Partially meets requirement |
| 1 | Does not meet requirement |
| 0 | Cannot assess from resume |
Assessment Framework:
For Each Resume:
Priority Matrix:
| Score Range | Action |
|---|---|
| 80-100% | Priority interview |
| 60-79% | Standard review |
| 40-59% | Conditional hold |
| <40% | Not qualified |
Input:
Job: Senior Product Manager
Requirements:
- 5+ years product management experience
- B2B SaaS background required
- Technical degree or equivalent experience
- Experience with Agile methodologies
- Preferred: MBA or similar
Resume:
Jane Smith
Product Manager at TechCorp (3 years)
- Led product roadmap for B2B analytics platform
- Managed team of 4 designers and engineers
- Increased user retention by 35%
Associate PM at StartupXYZ (2 years)
- B2C mobile app
- Launched 3 major features
Education: BS Computer Science, Stanford
Certifications: CSPO, SAFe Agilist
Output:
## Resume Screening: Jane Smith
### Quick Summary
**Position:** Senior Product Manager
**Candidate:** Jane Smith
**Score:** 78/100 - STANDARD REVIEW
---
### Must-Have Requirements
| Requirement | Status | Evidence |
|-------------|--------|----------|
| 5+ years PM experience | ✅ PASS | 3 + 2 = 5 years total |
| B2B SaaS background | ✅ PASS | TechCorp B2B analytics |
| Technical degree/equivalent | ✅ PASS | BS CS Stanford |
| Agile experience | ✅ PASS | CSPO, SAFe certifications |
**Must-Have Result:** PASS (4/4)
---
### Detailed Scoring
| Criterion | Weight | Score | Weighted | Notes |
|-----------|--------|-------|----------|-------|
| Years of Experience | 40% | 3/4 | 30/40 | Meets minimum exactly |
| B2B SaaS | 30% | 3/4 | 22.5/30 | 3 years, not full tenure |
| Technical Background | 15% | 4/4 | 15/15 | Stanford CS |
| Preferred (MBA) | 15% | 2/4 | 7.5/15 | Has certs, no MBA |
**Total Score: 75/100**
---
### Green Flags
| Flag | Evidence | Significance |
|------|----------|--------------|
| Quantified impact | "35% retention increase" | Results-oriented |
| Management experience | "Team of 4" | Leadership ready |
| Relevant certifications | CSPO, SAFe | Agile commitment |
| Top-tier education | Stanford CS | Technical foundation |
---
### Yellow Flags
| Flag | Concern | Mitigation |
|------|---------|------------|
| Experience exactly at minimum | Just hits 5 years | Probe depth in interview |
| Mixed B2B/B2C | 2 years in B2C | Understand B2B transition |
| No MBA | Preferred qualification | Certs may compensate |
---
### Red Flags
None identified.
---
### Interview Recommendation
**Decision:** RECOMMEND FOR INTERVIEW
**Rationale:**
- Meets all must-have requirements
- Strong B2B SaaS experience at TechCorp
- Technical background exceeds expectations
- Quantified achievements show impact
**Interview Focus Areas:**
1. Depth of B2B product strategy experience
2. Transition from B2C to B2B context
3. Scale of products managed (ARR, users)
4. Examples of cross-functional leadership
---
### Comparison Notes
Candidate is solid but not exceptional. Meets requirements without
significantly exceeding them. Consider alongside stronger candidates
if available.
Input:
Screen these 5 candidates for Marketing Manager:
Requirements: 3+ years marketing, B2B experience, analytics skills
1. Alice: 5 years B2B marketing, Google Analytics certified
2. Bob: 2 years marketing, B2C only, strong analytics
3. Carol: 4 years, mixed B2B/B2C, basic Excel
4. David: 6 years B2B, owns marketing analytics tool
5. Eve: 3 years B2B, HubSpot certified
Output:
## Batch Screening Summary: Marketing Manager
### Quick Rank
| Rank | Candidate | Score | Recommendation |
|------|-----------|-------|----------------|
| 1 | David | 95% | Priority Interview |
| 2 | Alice | 85% | Priority Interview |
| 3 | Eve | 75% | Standard Review |
| 4 | Carol | 55% | Conditional Hold |
| 5 | Bob | 40% | Not Qualified |
---
### Individual Summaries
#### 1. David (95%) - PRIORITY INTERVIEW
| Requirement | Status | Score |
|-------------|--------|-------|
| 3+ years | ✅ 6 years | 4/4 |
| B2B experience | ✅ Full tenure | 4/4 |
| Analytics skills | ✅ Tool owner | 4/4 |
**Standout:** Exceptional analytics depth - owns a marketing analytics tool
**Interview:** Immediately
---
#### 2. Alice (85%) - PRIORITY INTERVIEW
| Requirement | Status | Score |
|-------------|--------|-------|
| 3+ years | ✅ 5 years | 4/4 |
| B2B experience | ✅ Full tenure | 4/4 |
| Analytics skills | ✅ GA certified | 3/4 |
**Standout:** Solid all-around, Google Analytics certification
**Interview:** This week
---
#### 3. Eve (75%) - STANDARD REVIEW
| Requirement | Status | Score |
|-------------|--------|-------|
| 3+ years | ✅ Exactly 3 | 3/4 |
| B2B experience | ✅ Full tenure | 4/4 |
| Analytics skills | ⚠️ HubSpot only | 2/4 |
**Concern:** HubSpot is automation, not analytics
**Interview:** Probe analytics skills deeper
---
#### 4. Carol (55%) - CONDITIONAL HOLD
| Requirement | Status | Score |
|-------------|--------|-------|
| 3+ years | ✅ 4 years | 3/4 |
| B2B experience | ⚠️ Mixed | 2/4 |
| Analytics skills | ❌ Basic Excel | 1/4 |
**Concern:** Weak analytics foundation
**Hold:** Consider if top candidates decline
---
#### 5. Bob (40%) - NOT QUALIFIED
| Requirement | Status | Score |
|-------------|--------|-------|
| 3+ years | ❌ 2 years | 1/4 |
| B2B experience | ❌ B2C only | 1/4 |
| Analytics skills | ✅ Strong | 3/4 |
**Disqualified:** Does not meet experience or B2B requirements
**Action:** Reject with positive note on analytics skills
---
### Screening Actions
| Action | Candidates |
|--------|------------|
| Schedule interviews | David, Alice |
| Standard queue | Eve |
| Hold file | Carol |
| Rejection email | Bob |
Follow-up Prompts:
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Measure and optimize growth using the AARRR (Pirate Metrics) framework with stage-specific KPIs and funnel analysis
日本語の概要は準備中です。原文の説明を表示しています。
Calculate A/B test statistical significance. Use when: determining if test results are significant; calculating required sample size; estimating test duration; analyzing conversion experiments; making data-driven decisions
日本語の概要は準備中です。原文の説明を表示しています。
Assess customer account health using product usage, support sentiment, payment status, and relationship signals
日本語の概要は準備中です。原文の説明を表示しています。
Analyze paid advertising performance across channels and recommend budget reallocation to maximize ROAS and minimize CAC. Use when: planning quarterly ad budget allocation, diagnosing underperforming ad channels, deciding whether to scale spend on a channel, calculating marginal ROI across Google Ads, Meta, LinkedIn, or TikTok, rebalancing media mix after performance shifts, or setting up a test-and-scale framework for new channels.
日本語の概要は準備中です。原文の説明を表示しています。
Use when testing skills, commands, or agents for quality. Use after creating new skills, before deploying agents, or when debugging inconsistent agent behavior. Triggers on "evaluate", "test quality", "is this skill working", or QA of AI workflows.
日本語の概要は準備中です。原文の説明を表示しています。
Use when analyzing server logs to understand how AI crawlers (GPTBot, ClaudeBot, PerplexityBot) interact with your site. Use when optimizing content placement for LLM retrieval, diagnosing why AI search isn't citing your content, or auditing crawl patterns to find optimization gaps.
日本語の概要は準備中です。原文の説明を表示しています。