portfolio-deal-linker

Compare original and translation side by side

🇺🇸

Original

English

🇨🇳

Translation

Chinese

<objective> Automatically connect closed HubSpot deals to the skills, automations, and outreach actions that contributed to them. Builds a living GTME portfolio that proves Tim's operational leverage — time saved, revenue influenced, cost-per-deal, and automation ROI. This is career-critical evidence for the VP Business Development transition. </objective>

<quick_start> Daily automated run (7am CST): Checks for deals closed since last run → attributes to skills/actions → updates portfolio

On-demand: "portfolio update" → runs full attribution scan now "what did I influence this month" → generates monthly impact report "gtme evidence" → formats portfolio for interview/review context

Trigger phrases:

"portfolio update" / "deal closed"
"link deal to portfolio" / "gtme evidence"
"what did I influence" / "career evidence"
"transition tracker" / "show my impact" </quick_start>

<success_criteria>

Every closed-won deal attributed to originating skill/workflow within 24 hours
Revenue influenced tracked with clear attribution chain
Time-saved metrics aggregated weekly (skills that eliminated manual work)
Portfolio evidence formatted for VP BD transition narrative
Monthly executive summary auto-generated
Zero missed attributions on deals Tim touched </success_criteria>

<objective> 自动将已完成的HubSpot交易与对其有贡献的技能、自动化流程及客户拓展动作关联起来。构建动态GTME投资组合，证明Tim的运营杠杆作用——节省的时间、影响的收入、单位交易成本及自动化投资回报率。这是商务发展副总裁（VP BD）转型的关键职业证明材料。 </objective>

<quick_start> 每日自动运行（美国中部时间上午7点）： 检查自上次运行以来完成的交易→归因至对应技能/动作→更新投资组合

按需触发： "portfolio update"→立即执行完整归因扫描 "what did I influence this month"→生成月度影响报告 "gtme evidence"→为面试/评审场景格式化投资组合内容

触发短语：

"portfolio update" / "deal closed"
"link deal to portfolio" / "gtme evidence"
"what did I influence" / "career evidence"
"transition tracker" / "show my impact" </quick_start>

<success_criteria>

所有成交交易需在24小时内归因至发起技能/工作流
影响收入需通过清晰的归因链路追踪
每周汇总节省时长指标（消除手动工作的技能）
投资组合证明材料需适配VP BD转型叙事场景
自动生成月度高管摘要
Tim参与的交易无归因遗漏 </success_criteria>

Architecture

架构

SCHEDULED (7am CST)           ATTRIBUTION                 PORTFOLIO UPDATE
──────────────────────────────────────────────────────────────────────────────
HubSpot: recently closed  →  Match deal to skill that  →  Update portfolio.jsonl
deals (won + lost)        →  originated/influenced it  →  Update weekly digest
                          →  Calculate metrics         →  Update GTME narrative
                          →  Compare to manual baseline →  Career evidence file

SCHEDULED (7am CST)           ATTRIBUTION                 PORTFOLIO UPDATE
──────────────────────────────────────────────────────────────────────────────
HubSpot: recently closed  →  Match deal to skill that  →  Update portfolio.jsonl
deals (won + lost)        →  originated/influenced it  →  Update weekly digest
                          →  Calculate metrics         →  Update GTME narrative
                          →  Compare to manual baseline →  Career evidence file

Stage 1: Detect Newly Closed Deals

阶段1：检测新完成的交易

Use

hubspot_search_deals

with filters:

```
dealstage
```
IN ('closedwon', 'closedlost')

closedate

>= last run timestamp (stored in

~/.claude/portfolio/last-run.json

)

Exclude channel deals (
```
is_channel = true
```
) and owned by AE IDs '82625923', '423155215', '190030668' (Lex Evans, Ron Epstein, Phillip Sandler)

For each deal, pull:

Field	Purpose
`dealname`	Identification
`amount`	Revenue attribution
`closedate`	Cycle time calculation
`createdate`	Pipeline velocity
`dealstage`	Won vs lost
`hubspot_owner_id`	Tim's deals only
Associated contacts	Who was engaged
Associated company	Company match
Deal notes/activity	Attribution signals

使用

hubspot_search_deals

并应用以下筛选条件：

```
dealstage
```
属于 ('closedwon', 'closedlost')

closedate

≥ 上次运行时间戳（存储于

~/.claude/portfolio/last-run.json

）

排除渠道交易（
```
is_channel = true
```
）及由AE ID '82625923'、'423155215'、'190030668'（Lex Evans、Ron Epstein、Phillip Sandler）负责的交易

为每个交易提取以下信息：

字段	用途
`dealname`	交易标识
`amount`	收入归因
`closedate`	周期时长计算
`createdate`	管线流转速度
`dealstage`	成交/流失状态
`hubspot_owner_id`	仅Tim负责的交易
Associated contacts	关联联系人
Associated company	关联企业
Deal notes/activity	归因信号

Stage 2: Skill Attribution Engine

阶段2：技能归因引擎

For each closed deal, determine which skills/automations contributed:

为每个完成的交易确定贡献的技能/自动化流程：

Attribution Signals

归因信号

Signal	Skill Attributed	How to Detect
Contact was loaded via Apollo sequence	prospect-research-to-cadence	Apollo `emailer_campaigns_search` — check if contact was in a sequence
MEDDIC call prep was generated	meddic-call-prep-auto	Check if company appears in call prep logs
Deal was flagged by momentum analyzer	deal-momentum-analyzer	Check if deal appeared in RED/YELLOW actions
Contact enriched via Apollo	prospect-research-to-cadence	Apollo contact create date vs deal create date
Outreach email was drafted	prospect-research-to-cadence	Gmail draft history for contact email
Activity history exists	meddic-call-prep-auto	`ask_agent` — query activity timeline for company
Manual prospecting (no automation match)	Tim (manual)	Fallback — still counts for portfolio

信号	归因技能	检测方式
联系人通过Apollo序列导入	prospect-research-to-cadence	调用Apollo `emailer_campaigns_search` ——检查联系人是否在序列中
生成了MEDDIC通话准备材料	meddic-call-prep-auto	检查企业是否出现在通话准备日志中
交易被动量分析工具标记	deal-momentum-analyzer	检查交易是否出现在红/黄行动列表中
通过Apollo补充联系人信息	prospect-research-to-cadence	对比Apollo联系人创建时间与交易创建时间
生成了拓客邮件草稿	prospect-research-to-cadence	检查联系人邮箱对应的Gmail草稿历史
存在活动历史记录	meddic-call-prep-auto	调用 `ask_agent` ——查询企业的活动时间线
手动拓客（无自动化匹配）	Tim (manual)	兜底规则——仍计入投资组合

Attribution Model

归因模型

PRIMARY attribution (100% credit):
  → Skill that ORIGINATED the deal (first touch)

ASSIST attribution (shared credit):
  → Skills that INFLUENCED the deal (middle touches)
  → E.g., prospect-research found the contact, meddic-call-prep prepped the demo,
    deal-momentum flagged it when stalling

RECOVERY attribution:
  → If deal-momentum-analyzer flagged deal as RED/YELLOW
    AND deal subsequently closed-won
  → This is "recovered revenue" — strongest GTME evidence

PRIMARY attribution (100% credit):
  → Skill that ORIGINATED the deal (first touch)

ASSIST attribution (shared credit):
  → Skills that INFLUENCED the deal (middle touches)
  → E.g., prospect-research found the contact, meddic-call-prep prepped the demo,
    deal-momentum flagged it when stalling

RECOVERY attribution:
  → If deal-momentum-analyzer flagged deal as RED/YELLOW
    AND deal subsequently closed-won
  → This is "recovered revenue" — strongest GTME evidence

Stage 3: Calculate Portfolio Metrics

阶段3：计算投资组合指标

Per-Deal Metrics

单交易指标

Metric	Formula	Why It Matters
Cycle time	`closedate - createdate`	Pipeline velocity
Revenue	`amount`	Direct impact
Cost to close	Estimated from skill usage costs	Efficiency
Automation touches	Count of skill attributions	Leverage
Manual vs automated	% of deal lifecycle automated	Transition evidence

指标	计算公式	重要性
周期时长	`closedate - createdate`	管线流转效率
收入	`amount`	直接影响
成交成本	根据技能使用成本估算	效率评估
自动化触达次数	技能归因数量	杠杆作用
手动vs自动化占比	交易生命周期中自动化环节占比	转型证明材料

Aggregate Metrics (Rolling 30 days)

聚合指标（滚动30天）

Metric	Formula	Target
Total revenue influenced	Sum of attributed closed-won deals	Track monthly
Deals recovered	Deals flagged RED/YELLOW → closed-won	5-10% of pipeline
Time saved (hours/month)	Sum of skill time-saved estimates × usage count	30+ hrs/mo
Cost per deal	Total automation cost / deals closed	< $5/deal
Automation coverage	Deals with ≥1 skill touch / total deals	> 80%
Win rate lift	Automated deal win rate vs manual baseline	Track delta

指标	计算公式	目标值
影响总收入	归因成交交易的金额总和	月度追踪
挽回交易数	标记为红/黄后成交的交易数	管线的5-10%
节省时长（小时/月）	技能节省时长估算值 × 使用次数之和	30+小时/月
单位交易成本	总自动化成本 / 成交交易数	< $5/交易
自动化覆盖率	至少关联1项技能的交易数 / 总交易数	> 80%
成交率提升	自动化交易成交率 vs 手动基线	追踪差值

GTME Positioning Metrics

GTME定位指标

Metric	Narrative	VP BD Relevance
Revenue influenced/month	"I influenced $X in pipeline through automated workflows"	Revenue ownership
Hours saved/month	"Built systems that save 30+ hours/month of manual work"	Operational leverage
Cost per lead	"Reduced cost-per-qualified-lead from $X to $Y"	Unit economics
Recovery rate	"Recovered $18K/month in stalled pipeline through automated detection"	Pipeline management
Automation coverage	"80%+ of deals now touch at least one automated workflow"	Systems thinking

指标	叙事方向	VP BD相关性
月度影响收入	"我通过自动化GTM系统影响了$X的管线收入"	收入主导权
月度节省时长	"搭建的系统每月节省30+小时手动工作"	运营杠杆
单位线索成本	"将合格线索成本从$X降至$Y"	单位经济效益
挽回收入率	"通过自动化检测每月挽回$18K停滞管线收入"	管线管理
自动化覆盖率	"80%+的交易现在至少触达1个自动化工作流"	系统思维

Stage 4: Update Portfolio Files

阶段4：更新投资组合文件

4a. Append to portfolio.jsonl

4a. 追加至portfolio.jsonl

json

{
  "date": "2026-03-15",
  "deal_id": "hs_12345",
  "deal_name": "Baylor University",
  "amount": 45000,
  "outcome": "closedwon",
  "cycle_days": 32,
  "primary_skill": "prospect-research-to-cadence",
  "assist_skills": ["meddic-call-prep-auto", "deal-momentum-analyzer"],
  "recovered": true,
  "recovery_skill": "deal-momentum-analyzer",
  "automation_touches": 5,
  "manual_touches": 3,
  "automation_pct": 0.625
}

json

{
  "date": "2026-03-15",
  "deal_id": "hs_12345",
  "deal_name": "Baylor University",
  "amount": 45000,
  "outcome": "closedwon",
  "cycle_days": 32,
  "primary_skill": "prospect-research-to-cadence",
  "assist_skills": ["meddic-call-prep-auto", "deal-momentum-analyzer"],
  "recovered": true,
  "recovery_skill": "deal-momentum-analyzer",
  "automation_touches": 5,
  "manual_touches": 3,
  "automation_pct": 0.625
}

4b. Update Weekly Digest

4b. 更新每周摘要

Append deal to the existing

portfolio-artifact

weekly digest with attribution details.

将交易及归因详情追加至现有

portfolio-artifact

每周摘要中。

4c. Generate Monthly GTME Evidence Report

4c. 生成月度GTME证明报告

╔══════════════════════════════════════════════════════════════╗
║  GTME PORTFOLIO — [Month Year]                               ║
║  Tim Kipper | BDR → VP Business Development                  ║
╠══════════════════════════════════════════════════════════════╣

HEADLINE METRICS:
┌─────────────────────────────────────────────────────────────┐
│ Revenue Influenced:  $[XXX,XXX]  (XX deals)                 │
│ Pipeline Recovered:  $[XX,XXX]   (X deals saved from stall) │
│ Time Saved:          [XX] hours  ([X] min/day × [XX] days)  │
│ Automation Coverage: [XX]%       (deals with skill touch)    │
│ Cost per Deal:       $[X.XX]     (automation cost / deals)   │
└─────────────────────────────────────────────────────────────┘

SKILL ATTRIBUTION BREAKDOWN:
| Skill | Deals Influenced | Revenue | Time Saved |
|-------|-----------------|---------|------------|
| prospect-research-to-cadence | XX | $XX,XXX | XX hrs |
| meddic-call-prep-auto | XX | $XX,XXX | XX hrs |
| deal-momentum-analyzer | XX (recovered) | $XX,XXX | XX hrs |

TOP DEALS (with attribution chain):
1. [Deal] — $XX,XXX | Won
   Chain: Apollo enrich → sequence load → call prep → demo → close
   Skills: PRC → MCA → DMA

VP BD TRANSITION NARRATIVE:
"In [Month], I influenced $[X] in revenue through automated GTM systems
I designed and built. These systems saved [X] hours of manual work,
recovered $[X] in stalled pipeline, and achieved [X]% automation
coverage across the deal lifecycle. This demonstrates [operational
leverage / systems thinking / revenue ownership] at VP BD scale."

╚══════════════════════════════════════════════════════════════╝

</workflow>

<scheduled_automation>

╔══════════════════════════════════════════════════════════════╗
║  GTME PORTFOLIO — [Month Year]                               ║
║  Tim Kipper | BDR → VP Business Development                  ║
╠══════════════════════════════════════════════════════════════╣

HEADLINE METRICS:
┌─────────────────────────────────────────────────────────────┐
│ 影响收入:  $[XXX,XXX]  (XX笔交易)                 │
│ 挽回管线收入:  $[XX,XXX]   (X笔停滞交易被挽回) │
│ 节省时长:          [XX]小时  ([X]分钟/天 × [XX]天)  │
│ 自动化覆盖率: [XX]%       (关联技能的交易占比)    │
│ 单位交易成本:       $[X.XX]     (自动化成本/交易数)   │
└─────────────────────────────────────────────────────────────┘

技能归因明细:
| 技能 | 影响交易数 | 收入 | 节省时长 |
|-------|-----------------|---------|------------|
| prospect-research-to-cadence | XX | $XX,XXX | XX小时 |
| meddic-call-prep-auto | XX | $XX,XXX | XX小时 |
| deal-momentum-analyzer | XX (挽回) | $XX,XXX | XX小时 |

重点交易（含归因链路）:
1. [交易名称] — $XX,XXX | 成交
   链路: Apollo信息补充 → 序列导入 → 通话准备 → 演示 → 成交
   技能: PRC → MCA → DMA

VP BD转型叙事:
"在[月份]，我通过自主设计搭建的自动化GTM系统，影响了$[X]的收入。这些系统每月节省[X]小时手动工作，挽回$[X]停滞管线收入，实现了[X]%的交易全生命周期自动化覆盖率。这证明我具备VP BD层级的[运营杠杆/系统思维/收入主导]能力。"

╚══════════════════════════════════════════════════════════════╝

</workflow>

<scheduled_automation>

Daily 7am CST Run

每日美国中部时间上午7点运行

Schedule: Daily at 7:00 AM CST (13:00 UTC), weekdays Task name: "portfolio-deal-linker-daily" Flow:

Check HubSpot for deals closed since last run
Attribute each deal to originating skills
Calculate per-deal and aggregate metrics
Append to portfolio.jsonl
Update weekly digest if new closed-wons
Generate monthly report if month-end

Integration with EOD: When Tim says "EOD", include portfolio attribution summary for any deals closed today. </scheduled_automation>

调度规则: 工作日每日美国中部时间7:00（UTC时间13:00）运行 任务名称: "portfolio-deal-linker-daily" 流程:

检查HubSpot自上次运行以来完成的交易
将每个交易归因至发起技能
计算单交易及聚合指标
追加至portfolio.jsonl
若有新成交交易则更新每周摘要
月末生成月度报告

与EOD集成: 当Tim说"EOD"时，需包含当日完成交易的投资组合归因摘要。 </scheduled_automation>

Required MCP Tools

所需MCP工具

Epiphan CRM MCP: hubspot_search_deals, hubspot_get_deal, hubspot_search_contacts, hubspot_get_company, ask_agent (activity history for attribution)
Apollo MCP: apollo_emailer_campaigns_search (check sequence enrollment history)
Gmail MCP: gmail_search_messages (check draft/sent history for attribution)

Epiphan CRM MCP: hubspot_search_deals, hubspot_get_deal, hubspot_search_contacts, hubspot_get_company, ask_agent（用于归因的活动历史查询）
Apollo MCP: apollo_emailer_campaigns_search（检查序列加入历史）
Gmail MCP: gmail_search_messages（检查草稿/发送历史用于归因）

Sibling Skills Referenced

关联兄弟技能

```
portfolio-artifact-skill
```
— Base metrics capture, weekly digest format, executive summary template
```
deal-momentum-analyzer-skill
```
— Recovery attribution (deals flagged RED/YELLOW that closed-won)
```
prospect-research-to-cadence-skill
```
— Origination attribution (Apollo sequence enrollment)
```
meddic-call-prep-auto-skill
```
— Influence attribution (call prep generated for deal)
```
hubspot-revops-skill
```
— HubSpot query patterns, deal stage definitions

</dependencies>

```
portfolio-artifact-skill
```
— 基础指标采集、每周摘要格式、高管摘要模板
```
deal-momentum-analyzer-skill
```
— 挽回归因（标记为红/黄后成交的交易）
```
prospect-research-to-cadence-skill
```
— 发起归因（Apollo序列加入）
```
meddic-call-prep-auto-skill
```
— 影响归因（为交易生成通话准备材料）
```
hubspot-revops-skill
```
— HubSpot查询模式、交易阶段定义

</dependencies>