garrytan / garrytan/gstack

office-hours asks 'is demand real?' - an evidence layer that keeps the answer honest after the session

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Dominant language
TypeScript
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Forks
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Avg merge
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Merged PRs (30d)
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Description

`/office-hours` asks "is demand real?" six great ways, then the answer becomes a paragraph in a design doc. Three weeks later gbrain will faithfully recall that paragraph - but recall is not recheck, and the founder's day-one belief about demand ages silently while everyone is busy shipping.

I built the missing half and I'd rather compose with gstack than duplicate any of it: an open-source evidence layer (MIT, stdlib Python + MCP) where office-hours' answers become falsifiable claims instead of prose:

- **"demand reality"** -> a customer-class claim on a typed evidence ladder (`buyer:signup 0.40 / reply 0.50 / call 0.65 / signature 0.85 / payment 0.95`) - the tool caps confidence at the evidence tier, so a hot waitlist can't masquerade as proven revenue, and the verdict line carries a derived `demand-UNVALIDATED` stamp that regenerates on every write until real buyer evidence exists.
- **"narrowest wedge, learn from real usage"** -> the wedge's smoke test (landing page + waitlist + ads, outreach, preorder) with its pass bar pre-registered into the thesis *before* the experiment runs.
- **design-doc assumptions** -> claims with pre-registered falsifiers, re-checked on later runs; `stale` nags when a shipped bet's kill-conditions have gone unexamined.

Receipts, since claims about rigor deserve them: we benchmarked it three times, pre-registered each round, and published all three headline nulls with raw outputs - what survived is durable structure (0 format failures vs 213 for prose), updates at 0.54x the cost of re-narration, and zero fabricated evidence in 24 adversarial opportunities. The bug log ships in the repo (7 defects, each mapped to the invariant it earned). 30-second demo: `python tools/ledger.py demo`.

Repo: https://github.com/umair-tareen/rnd-skill - handoff mapping written up in [docs/USING_WITH_GSTACK.md](https://github.com/umair-tareen/rnd-skill/blob/main/docs/USING_WITH_GSTACK.md).

Concrete proposal, smallest first:
1. A line in USING_GBRAIN_WITH_GSTACK.md (or wherever ecosystem pointers live) noting the office-hours -> evidence-ledger handoff for people who want their design doc's assumptions tracked;
2. If there's appetite: office-hours optionally emits its six answers in a claims-shaped block so any evidence tool (mine or otherwise) can ingest them without parsing prose.

If neither fits gstack's direction, no hard feelings - closing this with "not our lane" is a perfectly good outcome, and the compat doc on my side works regardless. Happy to PR either option.

Contributor guide

Open the contributing guide

Research direction

Read docs/USING_WITH_GSTACK.md and inspect the repository's ecosystem-pointer documentation and /office-hours entry point. Decide whether the accepted scope is a pointer or claims-shaped output; done means the chosen integration path is documented or implemented with its expected handoff behavior clear and verified.

Written by the indexing model from the issue text.

Assessment

Tech stack
python, typescript
Domain
developer-experience, documentation
Issue type
Feature
Difficulty
4/5
Estimated time
3-5 days
Activity status
Quiet
Clarity
Mostly clear
Newbie friendliness
42/100

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