Getting started
pip install pulp-sdk
Docs
sample.txt2 paras · 160 chars
Sections
§1 Introduction
Paras
¶1: first paragraph block
¶2: second paragraph block
Sentences
S1S2S3S4
Clauses
C1C2C3C4C5C6
Claims
Claim 1Claim 2Claim 3
Phrases
NPVPNPVPPPNP
Named Entities
Pulp [ORG]
Words
ifwewaitforcertaintywewillbe+20 more
Characters
0 → 159
Special Characters
spaces × 27punct × 8nbsp × 0
Special Patterns
0 patterns detected
RootCause
Ethos
—
Pathos
—
Logos
—
Kairos
—
Style
—
Clarity
—
Focus
—
Awareness
—
Persuasive Velocity—
StemReferences
CensusFECCongressFed. Reg.RegulationsLegiScanGovInfoGDELTCivicWikimediaData.govPodcast Idx
AdCanopy
rank
Demographics
life_stageyoung_adult
education_levelbachelors
locationurban
occupationtech
Psychographics
Impelling
Compelling
Repelling
Mindstate
alpha 10 Hzcalm
Environment
vision onhearing onsmell offtouch offtaste off
Memory
purchases 12content 48brands 5
Vision
motivationdesirefear
NectarRewards
define
PoisonIvy
apply
GrapeVine
post
WebSoil
heatmap
DomainCrust
price
CodeMantle
trace
ServerCore
uptimeresize
WarpDisplays
q3-report.pdf
chart.png
keynote.mp4
WeftConversations
ThreadsChatInlineSide panels
DyeMedia
TextToday
ImageToday
SoundSoon
VideoSoon
BightInteractions
MouseKeyboardVoice · soonCombos · soon
Production
Coming soon
Psychographics
What they value and how they decide: risk posture, trust defaults, authority weighting, and the evidence types they find native. Two staffers with identical Demographics will split on the same memo because one trusts institutions and one trusts outsiders. This is the space that knows which is which.
createreadupdatedelete
| Verb | Signature | Description |
|---|---|---|
create | create(spec) | Initialize this class of state for a persona |
read | read() | Return the current state snapshot |
update | update(patch) | Apply a typed, domain-checked patch to the state |
delete | delete() | Remove this class of state from the persona |
from pulp import windfall
p = windfall.trueaura.persona(frame="urban_parents")
state = p.psychographics.read()
print(state.risk_posture)
p.psychographics.update(# typed patch, domain-checked)