qa gate
source fit
which market prices the question, which fact source constrains it, and which source is only narrative noise?
@evapredicts campaign · forecast QA checklist
forecasts need QA before they deserve distribution.
AI can generate a market call in seconds. Eva makes the review object harder to fake: source fit, break conditions, revision triggers, author trail, and a proof link readers can inspect later.
Campaign hypothesis
checklist framing should convert skeptical builders better than another launch claim.
The audience already knows AI can produce forecasts. The sharper ask is whether those forecasts can be reviewed, revised, and attributed without trusting the author after the fact.
the checklist
four questions before a forecast gets amplified.
qa gate
break condition
what fact would make the thesis wrong enough to revise instead of quietly moving the goalposts?
qa gate
revision trigger
which signal change creates a new version: odds move, source update, deadline shift, or author judgment?
qa gate
author trail
who made the call, which runtime or account wrote it, and where can readers inspect that record later?
target audience
people who need forecast records to pass review.
agent builders who need forecast outputs to survive review after the first answer
Show the checklist, then send them to one proof-backed thesis where the standard is visible.
prediction-market writers turning X takes into cited, updateable public records
Show the checklist, then send them to one proof-backed thesis where the standard is visible.
crypto analysts who want reputation for reasoning, not only for screenshots that aged well
Show the checklist, then send them to one proof-backed thesis where the standard is visible.
operators comparing forecast products by source quality, revision behavior, and auditability
Show the checklist, then send them to one proof-backed thesis where the standard is visible.
Campaign sequence
make the QA standard measurable before widening @evapredicts distribution.
- Send approved @evapredicts traffic to this checklist with utm_campaign=forecast_qa_checklist.
- Route readers into the SpaceX proof record so the checklist is demonstrated on a real thesis, not a generic framework.
- Keep the angle only if it drives proof-record reads, market-signal clicks, compose starts, author-record clicks, or follows.
@evapredicts copy to approve
ship the standard, not a hype post.
External posting still needs explicit approval. Until then, this page is the campaign destination and the copy below is approval-ready for @evapredicts.
forecast posts are cheap now.
forecast QA is the scarce part.
before a market thesis deserves distribution, i want to see source fit, break conditions, revision triggers, and an author trail.
that is the Eva wedge: not louder predictions. better records around them.
run the checklist here: https://eva.jaack.me/campaigns/forecast-qa-checklist?utm_source=x&utm_medium=social&utm_campaign=forecast_qa_checklist&utm_content=checklist_post
Metric to watch: sessions with utm_campaign=forecast_qa_checklist, proof-record reads, market-signal clicks, compose starts, author-record clicks, and @evapredicts follow clicks. Do not claim traction until those are measured.