Bijux Phylogenetics Product Guide

This handbook explains the public runtime in product terms: what the repository owns, how the capability families fit together, which interfaces are stable, how to operate them, and how to read their quality boundaries without flattening everything into one vague claim.

Use it when you want the product answer first without losing the source-tree depth behind that answer.

flowchart TD
    A[Start with a product question] --> B[What is this runtime for?]
    A --> C[How is it organized?]
    A --> D[Which interface should I use?]
    A --> E[How do I run it?]
    A --> F[How much should I trust a result?]
    B --> G[Foundation]
    C --> H[Architecture]
    D --> I[Interfaces]
    E --> J[Operations]
    F --> K[Quality]

Documentation home Runtime purpose and scope Architecture and package roles Public interfaces Installation and workflows Quality and release limits

What The Runtime Already Makes Possible

The checked-in runtime already spans:

• tree inspection, comparison, support handling, rootedness review, and rendering
• alignment validation, trimming, translation, and dataset preparation
• native finite-state likelihood plus native maximum-likelihood and supported native Bayesian public surfaces
• comparative regression, phylogenetic signal, discrete evolution, diversification, and ancestral reconstruction
• explicit parsimony, simulation, datasets, benchmark corpora, and review-facing report generation

Runtime Capability Atlas

Capability family	What this handbook should help a reader discover
Tree and alignment runtime	owned semantics, validation paths, comparison surfaces, and reportable artifacts
Native inference runtime	locally owned likelihood and inference contracts rather than only wrapped executables
Comparative runtime	PGLS, signal, regression, ancestral, discrete-evolution, and diversification families
Workflow runtime	CLI and typed Python routes that emit durable artifacts
Trust runtime	benchmarks, validation lanes, evidence links, and release-facing quality reading

Why This Is Not A Small Wrapper Layer

flowchart LR
    A[Canonical runtime] --> B[Trees and alignments]
    A --> C[Native likelihood and inference]
    A --> D[Comparative and ancestral analysis]
    A --> E[Reports, bundles, and artifacts]
    A --> F[Benchmarks and validation]

The runtime is larger than a "FASTA to tree" wrapper story. It owns a real tree runtime, lower-level likelihood contracts, benchmark surfaces, typed workflow results, and substantial comparative-analysis families. This handbook keeps that depth visible while also keeping evidence limits visible.

Read By Question

• What is this repository trying to do, and what is it refusing to claim? Start with Foundation.
• Which package or capability family owns a surface? Start with Architecture.
• Which entry point should I use for my task? Start with Interfaces.
• How do I install the runtime and run practical workflows? Start with Operations.
• How do I judge trust, release posture, and limits? Start with Quality.

Flagship Guides

• Surface selection guide
• Native maximum-likelihood workflows
• Native Bayesian workflows
• Native benchmark review
• Validation lanes
• Claim reading guide

Read This Handbook Like A Map

1. Start with Foundation to understand what the runtime is claiming and refusing to claim.
2. Continue to Architecture to understand which package and capability family owns what.
3. Use Interfaces to choose the right public surface.
4. Use Operations to run the package in the right mode.
5. Finish with Quality to understand how strong the proof surface really is.

Related Reading

• Use the Evidence book when the question is study evidence, parity, freshness, or coverage gaps.
• Use the Maintainer handbook when the question is release stewardship, documentation alignment, or repository health.