ShipSignal — AI impact

crown · 2026-02-05 → 2026-06-17 · 19.0 weeks · 723 dev commits · excluded 3 merges + 0 maintenance-bot
AI Adoption
Pervasive97%
Claude 704 · lower bound
Delivery Health
55/100 F
general eng norms
Readiness
83/100 B
static repo state
How to read this report
AI Adoption
The share of commits an AI tool co-authored — the one directly measured sign AI is actually being used here, not a survey.
Delivery Health
How sound the team's shipping habits are by general engineering norms — deliberately NOT credited to AI. High adoption means little if delivery health is poor.
Readiness
Whether the repo is set up so an AI agent (or a new human) can navigate it and trust what it reads — the conditions that decide whether AI adoption actually pays off.
Before/after AI Enablement
When a clean pre-AI baseline exists, how delivery metrics shifted after adoption — shown as context, never proof AI caused the change.
Trajectory
How AI adoption and delivery health moved over the repo's history — two parallel timelines, correlation only, never proof one caused the other.
AI adoption 97.4% (704/723 commits — lower bound)
Adoption date: 2026-02-02
Rate / week: ███▇█▇████████▇████
The share of commits an AI tool co-authored — the one directly measured sign AI is actually being used here, not a survey.

Delivery Health

How sound the team's shipping habits are by general engineering norms — deliberately NOT credited to AI. High adoption means little if delivery health is poor.

change_size_discipline
100%
test_discipline
10% low test discipline
knowledge_distribution
n/a (solo author)

Context (not scored): fix/revert 26% · 38.05 commits/wk · 1 contributors.

Before/after AI Enablement (bonus)

n/a — AI adoption is at or before repo inception — no pre-AI window to compare
A before/after needs a clean pre-AI baseline; the three numbers above stand on their own.

Trajectory over time — parallel timelines, NOT a causal link

0501002026-02-052026-06-15adoption %delivery health
Attribution caveat. Delivery pillars (flow, quality, risk) measure GENERAL delivery health — only AI-adoption and readiness are AI-specific. A delivery change may come from hiring, a finished migration, or a calmer quarter. The score asks whether the conditions under which AI pays off are improving — it does NOT prove AI caused any change.

shipsignal v0.1.6 · 2026-06-20T22:19:22Z

Readiness — 83/100 · B

entry_point
20/20
agent_instructions
15/15
module_coverage
13.3/20
setup_tooling
9.4/20
doc_integrity
13/13
doc_freshness
12/12

Top Readiness fixes (4 total)