General
PromptBeginner5 minmarkdown
- **Urgency language (ASAP
immediate)** = Pain is acute
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General
PromptBeginner5 minmarkdown
- **3+ relevant roles posted** = Active initiative
budget allocated
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General
PromptBeginner5 minmarkdown
relationship: {is_followup: True
last_outcome: neutral}
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General
PromptBeginner5 minmarkdown
- [ ] Employee count (LinkedIn
website)
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General
PromptBeginner5 minmarkdown
print(json.dumps(result
indent=2))
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General
PromptBeginner5 minmarkdown
signals: [recent_funding
job_postings_relevant]
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General
PromptBeginner5 minmarkdown
relationship: {is_followup: False
mutual_connections: 2}
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General
PromptBeginner5 minmarkdown
timing_signals: [just_funded
active_evaluation]
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General
PromptBeginner5 minmarkdown
size_indicators: {employees: 200
revenue: 25_000_000}
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General
PromptBeginner5 minmarkdown
for i
prospect in enumerate(scored
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General
PromptBeginner5 minmarkdown
scored.sort(key=lambda x: x.raw_score
reverse=True)
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General
PromptBeginner5 minmarkdown
is_followup=prospect.get(relationship
{}).get(is_followup
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General
PromptBeginner5 minmarkdown
) -> dict[str
Any]:
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General
PromptBeginner5 minmarkdown
scored = [calculate_priority_score(p
weights) for p in prospects]
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General
PromptBeginner5 minmarkdown
timing: {score: timing_score
reason: timing_reason}
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General
PromptBeginner5 minmarkdown
signals: {score: signal_score
reason: signal_reason}
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General
PromptBeginner5 minmarkdown
warmth: {score: warmth_score
reason: warmth_reason}
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General
PromptBeginner5 minmarkdown
priority_rank=0
# Will be set after sorting
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General
PromptBeginner5 minmarkdown
deal_size: {score: deal_score
reason: deal_reason}
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General
PromptBeginner5 minmarkdown
raw_score=round(raw_score
2)
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General
PromptBeginner5 minmarkdown
company=prospect.get(company
Unknown)
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General
PromptBeginner5 minmarkdown
call_time=prospect.get(call_time
Unknown)
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General
PromptBeginner5 minmarkdown
contact=prospect.get(contact
Unknown)
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General
PromptBeginner5 minmarkdown
signal_score
signal_reason = score_signals(prospect)
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