MaintainerPulse

temporal prediction of dependency maintenance risk

jsonschema-specifications python-jsonschema/jsonschema-specifications ● elevated

47%
no release in the next 12 months
46%
new issues will go unanswered (30 days)
74%
maintainer activity collapse within 12 months
32%
chance of a release within 12 months (survival model)

Model risk over time

calibrated P(no release next 12mo) at each historical monthly snapshot
0%50%100%2023-072024-032024-102025-06high risk

Repository activity, last 36 months

pushes issues PyPI release
010202023-112024-112025-102026-10

What drives this score

TreeSHAP contributions; raises risk / lowers risk
releases, all time-releases, last 12mo+new stars, 12mo+months since last push-

Survival curve

P(still no release) m months ahead, discrete-time hazard model
0%50%100%036912

What if? — poke the model

drag a signal and the deployed models rescore this package live (implied signals move together — two years without a release also zeroes "releases, last 12mo"). The needle tracks the activity-collapse model, a logistic regression: monotone by construction, so it responds smoothly to counterfactuals where the tree models step.

maintainer activity collapse, 12mo

In plain words

Maintained alternatives

similar packages with low predicted risk; ranked by summary similarity blended with shared-dependents overlap, validated against known migrations
packagewhat it issimilarity shared dependentsits 12mo risk
jsonschema An implementation of JSON Schema validation for Python 0.71 5 9%
weblate-schemas A collection of JSON schemas used by Weblate 0.71 0 6%
jsonschema-path JSONSchema Spec with object-oriented paths 0.67 0 5%
json5 A Python implementation of the JSON5 data format. 0.53 2 17%
json-repair A package to repair broken json strings 0.53 1 5%

Signals at the latest snapshot

days since last release 419 releases, last 12mo 0
people pushing, last 12mo 1 bus factor (top pusher share) 100%
issues opened, last 12mo 1 30-day response rate 0%
stars accumulated 14 open vulns without fix 0

Probabilities are isotonic-calibrated on a held-out validation year and evaluated on future snapshots the models never saw (PR-AUC 0.894, precision@50 = 1.00 on the headline target).