portfolio-deal-linker by scientiacapital/skills

<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>

Architecture

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

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 IDs '82625923', '423155215'

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

Stage 2: Skill Attribution Engine

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

Attribution Signals

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

Attribution Model

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

Per-Deal Metrics

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

Aggregate Metrics (Rolling 30 days)

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

GTME Positioning Metrics

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

Stage 4: Update Portfolio Files

4a. Append to portfolio.jsonl

{
  "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

Append deal to the existing portfolio-artifact weekly digest with attribution details.

4c. Generate Monthly GTME Evidence Report

╔══════════════════════════════════════════════════════════════╗
║  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."

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

<scheduled_automation>

Daily 7am CST Run

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>

Sibling Skills Referenced

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