Built-in adapters, a plugin system for extensions, and an open ecosystem. Any tool with project data can become an adapter.
Ships with Evolution Engine. Zero config, auto-detected from your repo.
Local git history analysis — commits, file changes, co-change patterns.
Python dependency tracking from requirements.txt and Pipfile.lock.
Node.js dependency tracking from package-lock.json with depth analysis.
Go module tracking from go.sum with dependency depth.
Rust crate tracking from Cargo.lock with depth analysis.
Ruby gem tracking from Gemfile.lock.
PHP dependency tracking from composer.lock.
API schema change tracking from OpenAPI/Swagger specs.
Infrastructure-as-code change tracking from .tf files.
Container config change tracking from Dockerfiles and compose files.
Local CI workflow analysis from GitHub Actions, GitLab CI, Jenkins, and CircleCI config files.
CI pipeline monitoring — run duration, failure rates, workflow trends.
Release cadence tracking, pre-release detection, asset monitoring.
Reads security advisory data from repos that use Dependabot alerts.
GitLab CI/CD pipeline monitoring via API.
GitLab release cadence tracking via API.
CircleCI pipeline and workflow monitoring.
Error tracking — event count, user impact, unhandled errors.
Test results — total tests, failure rate, skip rate, suite duration.
Code coverage — line rate, branch rate from Cobertura XML reports.
Install any adapter via pip. Build your own in minutes. Plugins are auto-discovered at runtime.
Third-party adapters are regular pip packages. Install one and EE discovers it automatically on the next run.
pip install evo-adapter-jenkins
evo analyze .
# → Detected: git, pip, jenkins (plugin)
Scaffold a new adapter in one command. Implement iter_events(), validate, and publish.
evo adapter new myapp --family ci
cd evo-adapter-myapp
# implement iter_events() ...
evo adapter validate evo_myapp.MyAppAdapter
pip install -e .
Read the Guide
Reads Python test coverage data (coverage.xml). A working example of a file-based adapter.
pip install evo-adapter-pytest-cov
evo adapter list . # → [community] testing/pytest_cov
evo analyze . # → Ingesting from plugin...
Reads Jest coverage-summary.json. Shows the same pattern for JavaScript projects.
pip install evo-adapter-jest-cov
evo adapter list . # → [community] testing/jest_cov
evo analyze . # → Ingesting from plugin...
EE automatically finds adapters for tools you use, notifies you about updates, and keeps your knowledge base current. No manual checking needed.
EE scans your repo for known tools and checks PyPI for matching adapters. Run one command to see what's available:
evo adapter discover .
# Available adapters:
# evo-adapter-datadog v1.0.0
# evo-adapter-sentry v0.2.0
# Install all: pip install ...
After each analysis, EE checks for adapter updates and new adapters matching your tools. Notifications appear inline:
evo analyze .
# ... analysis output ...
# Notifications:
# Update: evo-adapter-sentry
# 0.1.0 → 0.2.0
Opt into auto-pulling community-discovered patterns. Your knowledge base stays current without manual intervention:
evo config set sync.auto_pull true
evo analyze .
# Auto-pulled 5 community patterns
# "Observed across 9 projects"
Privacy by design: All checks use the public PyPI API — no authentication needed, no data sent from your machine. Cached for 24 hours to minimize network requests. Respects DO_NOT_TRACK=1 and can be fully disabled with evo config set adapter.check_updates false.
EE already detects these tools in your repo via prescan. Community adapters coming soon — or build one yourself.
APM metrics, error rates, deployment markers
Application performance and error monitoring
Dashboard metrics and alerting data
Metrics collection and alerting
Vendor-neutral observability framework
Application Insights and Azure diagnostics
Elasticsearch-based application monitoring
Incident frequency, MTTR, escalation patterns
Alert management and on-call data
Vulnerability and license compliance data
Static analysis and security scanning
Quality gate status and code metrics
Code coverage tracking and reporting
Cycle time, WIP count, sprint velocity
Issue tracking and project management
AI-powered code review findings
Automated code review insights
Feature flag state and rollout data
Open-source feature flag management
...and any other tool with project data. The list above is non-exhaustive.
We prioritize adapters by community demand. Tell us what you need, or build one yourself.