Dataset · Cold Start Data

Every repository that went viral, and what happened to it after.

On June 30, 2026, GitHub restricted the API that told you when a repository's stars arrived. The public event archive still records every one of them, so we pulled the cohort ourselves: all 195 repositories created between January 2023 and June 2025 that gained 5,000 or more stars within 60 days of creation, and their outcomes twelve months on.

This is the whole measurement — the frozen pre-registration, the as-run method with every deviation from it, the raw pulls, and the four scripts that produced the numbers. It backs the episode “We Tracked Every Viral AI Repo. Most Stars Predict Nothing.” on Cold Start Data.

Measured 2026-08-27195 repositoriesPre-registeredRe-runnable

What it found

195

repositories in the cohort

Every public repo created between 2023-01-01 and 2025-06-30 that gained 5,000 or more stars within 60 days of creation. Nine of them no longer exist at all.

0.2%

median human commit activity at month 12, as a share of peak

95% CI 0.0–3.0, n=168 with commit data. 54.3% recorded zero human commits in month twelve. The confidence interval is wide and we report it rather than the point estimate alone.

≤4.3%

of the variance in any health measure explained by launch-week stars

R² on log-transformed values, across commits, contributors, releases, stars today, and still-alive. The rank correlations run slightly negative — more launch-week stars, marginally worse outcomes.

Two numbers in the episode carry a deliberate split: the AI share of the cohort is 59.0% under the rubric frozen before the pull, and 79.5% under a documented manual audit that catches what 2026 metadata hides. The pre-registered number is the one we quote; the audit is published beside it so you can see the gap and judge it yourself.

The dataset

Start with the README — it carries the method and the deviations.

README.md9 KBThe as-run method in full, including the complete list of deviations from the pre-registration.
PRE-REGISTRATION.md1 KBThe sample design, frozen before any data was pulled and reproduced verbatim.
cohort.csv40 KBThe final cohort, one row per repository — pre-registered columns first, derived columns after.
excluded_candidates.csv12 KBDiscovery candidates that failed the creation-window rule, each with its reason.
ai_label_borderline_calls.json22 KBEvery borderline call made by the frozen AI-labeling rubric, with the evidence behind it.
ai_label_manual_review.json6 KBThe secondary audit layered on the rubric — every override and every judgment call left standing, with reasons.
results.json3 KBThe four result blocks the episode narrates, machine-readable.
results.md6 KBThe same numbers written out with the caveats attached to each.

Raw pulls

Unmodified, as fetched on 2026-08-27. The discovery and outcome scripts re-run against live sources, so exact counts drift with time — this is the frozen snapshot the episode was built on.

raw/daily_series.tsv3.2 MBDaily star counts per repository from the public event archive — the series everything else is derived from.
raw/cohort_broad.tsv13 KBThe unfiltered discovery pull, before the creation-window rule was applied.
raw/createvent_creations.tsv3 KBRepository creation timestamps as recorded in the event stream.
raw/search_crosscheck.tsv143 KBThe independent Search API route, run as the pre-registered cross-check.
raw/repo_meta.jsonl105 KBREST metadata for every cohort repository, as served on the run date.
raw/outcomes.jsonl225 KBGraphQL outcome pulls: commit history, contributors, releases, archival status.
raw/entries.jsonl150 KBThe assembled per-repository records the analysis reads.
raw/stargazers_restriction_test.json862 BThe test that documents what the June 2026 API restriction actually blocks.
raw/clickhouse_meta.txt115 BThe event-archive currency check: span and event count at run time.

Reproduction

Run in order. The first script needs no credentials at all.

scripts/01_discovery_clickhouse.py5 KBDiscovery against the public event archive. No token required.
scripts/02_search_crosscheck.py4 KBThe Search API cross-check. Needs a GitHub token.
scripts/03_outcomes_graphql.py15 KBOutcome measurement at T+6 and T+12. Needs a GitHub token.
scripts/04_analyze.py17 KBEverything downstream: cohort assembly, labeling, correlations, intervals.

Take it and argue with it

We publish the measurement because a finding nobody can check isn't a finding. Re-run it, extend the window, disagree with the labeling rubric — attribution is appreciated, and corrections more so. If you find an error, we'll fix it visibly, per our editorial standards.

hello@vantedgevault.com