product-manager-toolkit by sickn33/antigravity-awesome-skills
npx skills add https://github.com/sickn33/antigravity-awesome-skills --skill product-manager-toolkit现代产品管理从探索到交付的必备工具和框架。
python scripts/rice_prioritizer.py sample # 创建示例 CSV
python scripts/rice_prioritizer.py sample_features.csv --capacity 15
python scripts/customer_interview_analyzer.py interview_transcript.txt
references/prd_templates.md 中选择模板收集功能需求
使用 RICE 评分
# 创建包含以下字段的 CSV:name,reach,impact,confidence,effort
python scripts/rice_prioritizer.py features.csv
广告位招租
在这里展示您的产品或服务
触达数万 AI 开发者,精准高效
分析产品组合
生成路线图
进行访谈
分析洞察
python scripts/customer_interview_analyzer.py transcript.txt
提取内容:
* 痛点及其严重性
* 功能需求及其优先级
* 待完成的工作
* 情感分析
* 关键主题和引述
3. 综合发现
* 将相似的痛点分组
* 识别跨访谈的模式
* 映射到机会领域
4. 验证解决方案
* 创建解决方案假设
* 使用原型进行测试
* 衡量实际与预期行为
选择模板
构建内容结构
协作
具有产品组合分析功能的高级 RICE 框架实现。
功能 :
使用示例 :
# 基础优先级排序
python scripts/rice_prioritizer.py features.csv
# 使用自定义团队容量 (每季度人月)
python scripts/rice_prioritizer.py features.csv --capacity 20
# 输出为 JSON 以便集成
python scripts/rice_prioritizer.py features.csv --output json
基于 NLP 的访谈分析,用于提取可操作的洞察。
能力 :
使用示例 :
# 分析单个访谈
python scripts/customer_interview_analyzer.py interview.txt
# 输出为 JSON 以便聚合
python scripts/customer_interview_analyzer.py interview.txt json
适用于不同场景的多种 PRD 格式:
标准 PRD 模板
单页 PRD
敏捷史诗模板
功能简报
Score = (Reach × Impact × Confidence) / Effort
Reach: 用户数/季度
Impact:
- Massive = 3x
- High = 2x
- Medium = 1x
- Low = 0.5x
- Minimal = 0.25x
Confidence:
- High = 100%
- Medium = 80%
- Low = 50%
Effort: 人月
Low Effort High Effort
High QUICK WINS BIG BETS
Value [Prioritize] [Strategic]
Low FILL-INS TIME SINKS
Value [Maybe] [Avoid]
1. 背景问题 (5 分钟)
- 角色和职责
- 当前工作流程
- 使用的工具
2. 问题探索 (15 分钟)
- 痛点
- 频率和影响
- 当前的变通方法
3. 解决方案验证 (10 分钟)
- 对概念的反应
- 价值感知
- 支付意愿
4. 总结 (5 分钟)
- 其他想法
- 推荐
- 后续跟进许可
We believe that [building this feature]
For [these users]
Will [achieve this outcome]
We'll know we're right when [metric]
Outcome
├── Opportunity 1
│ ├── Solution A
│ └── Solution B
└── Opportunity 2
├── Solution C
└── Solution D
Acquisition → Activation → Retention → Revenue → Referral
Key Metrics:
- Conversion rate at each step
- Drop-off points
- Time between steps
- Cohort variations
此工具包可与以下系统集成:
# 优先级排序
python scripts/rice_prioritizer.py features.csv --capacity 15
# 访谈分析
python scripts/customer_interview_analyzer.py interview.txt
# 创建示例数据
python scripts/rice_prioritizer.py sample
# 用于集成的 JSON 输出
python scripts/rice_prioritizer.py features.csv --output json
python scripts/customer_interview_analyzer.py interview.txt json
此技能适用于执行概述中描述的工作流或操作。
每周安装量
1.6K
仓库
GitHub 星标数
27.4K
首次出现
Jan 19, 2026
安全审计
安装于
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Essential tools and frameworks for modern product management, from discovery to delivery.
python scripts/rice_prioritizer.py sample # Create sample CSV
python scripts/rice_prioritizer.py sample_features.csv --capacity 15
python scripts/customer_interview_analyzer.py interview_transcript.txt
references/prd_templates.mdGather Feature Requests
Score with RICE
# Create CSV with: name,reach,impact,confidence,effort
python scripts/rice_prioritizer.py features.csv
Analyze Portfolio
Generate Roadmap
Conduct Interviews
Analyze Insights
python scripts/customer_interview_analyzer.py transcript.txt
Extracts:
* Pain points with severity
* Feature requests with priority
* Jobs to be done
* Sentiment analysis
* Key themes and quotes
3. Synthesize Findings
* Group similar pain points
* Identify patterns across interviews
* Map to opportunity areas
4. Validate Solutions
* Create solution hypotheses
* Test with prototypes
* Measure actual vs expected behavior
Choose Template
Structure Content
Collaborate
Advanced RICE framework implementation with portfolio analysis.
Features :
Usage Examples :
# Basic prioritization
python scripts/rice_prioritizer.py features.csv
# With custom team capacity (person-months per quarter)
python scripts/rice_prioritizer.py features.csv --capacity 20
# Output as JSON for integration
python scripts/rice_prioritizer.py features.csv --output json
NLP-based interview analysis for extracting actionable insights.
Capabilities :
Usage Examples :
# Analyze single interview
python scripts/customer_interview_analyzer.py interview.txt
# Output as JSON for aggregation
python scripts/customer_interview_analyzer.py interview.txt json
Multiple PRD formats for different contexts:
Standard PRD Template
One-Page PRD
Agile Epic Template
Feature Brief
Score = (Reach × Impact × Confidence) / Effort
Reach: # of users/quarter
Impact:
- Massive = 3x
- High = 2x
- Medium = 1x
- Low = 0.5x
- Minimal = 0.25x
Confidence:
- High = 100%
- Medium = 80%
- Low = 50%
Effort: Person-months
Low Effort High Effort
High QUICK WINS BIG BETS
Value [Prioritize] [Strategic]
Low FILL-INS TIME SINKS
Value [Maybe] [Avoid]
1. Context Questions (5 min)
- Role and responsibilities
- Current workflow
- Tools used
2. Problem Exploration (15 min)
- Pain points
- Frequency and impact
- Current workarounds
3. Solution Validation (10 min)
- Reaction to concepts
- Value perception
- Willingness to pay
4. Wrap-up (5 min)
- Other thoughts
- Referrals
- Follow-up permission
We believe that [building this feature]
For [these users]
Will [achieve this outcome]
We'll know we're right when [metric]
Outcome
├── Opportunity 1
│ ├── Solution A
│ └── Solution B
└── Opportunity 2
├── Solution C
└── Solution D
Acquisition → Activation → Retention → Revenue → Referral
Key Metrics:
- Conversion rate at each step
- Drop-off points
- Time between steps
- Cohort variations
This toolkit integrates with:
# Prioritization
python scripts/rice_prioritizer.py features.csv --capacity 15
# Interview Analysis
python scripts/customer_interview_analyzer.py interview.txt
# Create sample data
python scripts/rice_prioritizer.py sample
# JSON outputs for integration
python scripts/rice_prioritizer.py features.csv --output json
python scripts/customer_interview_analyzer.py interview.txt json
This skill is applicable to execute the workflow or actions described in the overview.
Weekly Installs
1.6K
Repository
GitHub Stars
27.4K
First Seen
Jan 19, 2026
Security Audits
Gen Agent Trust HubPassSocketPassSnykPass
Installed on
opencode1.4K
gemini-cli1.4K
codex1.4K
cursor1.3K
github-copilot1.3K
amp1.1K