Skip to content
Data
Skill

/etetoolkit

Analyzes, manipulates, compares, annotates, and visualizes phylogenetic or other hierarchical trees with ETE 4. Supports Newick/Nexus tree I/O, topology edits and pattern matching, Robinson-Foulds comparisons, gene-tree evolutionary events and reconciliation, NCBI/GTDB taxonomy,

From plugin
scientific-agent-skills
56k177 skills

Claude Code

$ npx -y skills add K-Dense-AI/scientific-agent-skills --skill etetoolkit --agent claude-code

SKILL.md

etetoolkit.SKILL.md
name: etetoolkit
description: Analyzes, manipulates, compares, annotates, and visualizes phylogenetic or other hierarchical trees with ETE 4. Supports Newick/Nexus tree I/O, topology edits and pattern matching, Robinson-Foulds comparisons, gene-tree evolutionary events and reconciliation, NCBI/GTDB taxonomy, SmartView exploration, and publication rendering. Applies to existing trees after alignment and phylogenetic inference, rather than inferring trees from raw sequences.
license: GPL-3.0-or-later
allowed-tools: Read Write Edit Bash Python
compatibility: Bundled scripts require Python 3.10+ and ete4 4.4.0 (upstream metadata requires Python >=3.7). Public taxonomy acquisition needs internet access. SmartView uses a local browser/server; static PNG rendering needs ete4[render-sm] and Chrome/Chromium, and Qt PDF/SVG rendering needs ete4[treeview].
metadata:
  version: "3.0"
  last-reviewed: "2026-09-30"
  skill-author: K-Dense Inc.

ETE Toolkit 4

Scope

Use ETE 4 to work with an existing tree:

  • Read Newick/Nexus, then inspect, annotate, transform, root, prune, and write

Newick trees

  • Compare topologies and calculate phylogenetic distances
  • Find repeated subtree topologies with `TreePattern`
  • Analyze gene trees with `PhyloTree`
  • Query local NCBI or GTDB taxonomy databases
  • Explore large trees interactively with SmartView
  • Render PNG with SmartView or PNG/PDF/SVG with the optional Qt treeview

ETE does not replace sequence alignment or phylogenetic inference software. For raw sequences, first use MAFFT or another aligner and IQ-TREE 2, FastTree, or another inference tool; then load the resulting tree into ETE.

Current Target

This skill targets **ETE 4.4.0**, released September 3, 2025 and verified as the current PyPI release on September 30, 2026. Core, phylogeny, local synthetic taxonomy and helper checks target this released package, not unreleased upstream changes. See [`references/review.md`](references/review.md) for executed coverage and limitations.

Use `https://etetoolkit.github.io/ete/` for ETE 4 documentation. The `etetoolkit.org/docs/latest` pages are legacy ETE 3 documentation despite the URL name.

Do not silently translate these examples back to ETE 3:

  • Package and import: `ete4`, not `ete3`
  • File input: pass an open file object; use strings for Newick text and do not

rely on path-string heuristics retained in ETE 4.4.0

  • Newick selection: `parser=`, not `format=`
  • Node metadata: `props`, `add_prop()`, and `add_props()`
  • Iteration: `leaves()`, `descendants()`, and related methods return iterators
  • Predicates: `node.is_leaf` and `node.is_root` are properties, not methods
  • Node lookup: `tree["name"]`, not `tree & "name"`

For porting older code, load [`references/migration-ete3-to-ete4.md`](references/migration-ete3-to-ete4.md).

Installation

Install the pinned base package:

uv pip install "ete4==4.4.0"

Add only the visualization extra required by the workflow:

# SmartView static PNG screenshots
uv pip install "ete4[render-sm]==4.4.0"

# Legacy Qt renderer for PNG, PDF, and SVG
uv pip install "ete4[treeview]==4.4.0"

Confirm the active environment:

uv run --no-project --isolated --with "ete4==4.4.0" python -c "import ete4; print(ete4.__version__)"

No credentials are required. NCBI and GTDB workflows download public taxonomy data and can consume substantial disk space; see [`references/taxonomy.md`](references/taxonomy.md) before the first update.

Quick Start

from pathlib import Path

from ete4 import Tree

# Use an open file object for files; reserve strings for Newick text.
with Path("tree.nw").open(encoding="utf-8") as handle:
    tree = Tree(handle, parser=1)  # parser 1: internal node names

print(tree.to_str(props=["name", "dist"], compact=True))
print("Leaves:", list(tree.leaf_names()))

# Search and annotate.
focal = tree["species1"]
focal.add_props(host="human", status="focal")

# Keep selected tips while preserving pairwise branch-length distances.
tree.prune(
    ["species1", "species2", "species3"],
    preserve_branch_length=True,
)

# Root and serialize explicitly.
tree.set_midpoint_outgroup()
tree.write(
    outfile="processed.nw",
    parser=1,
    props=["host", "status"],
)

Choose the parser deliberately. A parser mismatch is the most common cause of `NewickError`, lost internal labels, or support values being read as names. See [`references/api_reference.md`](references/api_reference.md).

Core Workflows

Inspect and transform a tree

from ete4 import Tree

tree = Tree("((A:1,B:1)CladeAB:0.4,C:2)Root;", parser=1)

for node in tree.traverse("preorder"):
    label = node.name if node.name is not None else node.id
    print(label, node.level, node.is_leaf, node.dist)

tree["A"].add_prop("group", "case")
tree["B"].add_prop("group", "control")

mrca = tree.common_ancestor("A", "B")
print(mrca.name)

tree.write(
    outfile="annotated.nhx",
    parser=1,
    props=["group"],
    format_root_node=True,
)

Node names need not be unique. `tree["A"]` returns the first match; use `list(tree.search_nodes(name="A"))` and validate the count when duplicates are possible.

Compare two topologies

from ete4 import Tree

tree_a = Tree("((A,B),(C,D));")
tree_b = Tree("((A,C),(B,D));")

(
    rf,
    max_rf,
    common_leaves,
    edges_a,
    edges_b,
    discarded_a,
    discarded_b,
) = tree_a.robinson_foulds(tree_b)

normalized_rf = rf / max_rf if max_rf > 0 else None
print(rf, max_rf, normalized_rf, sorted(common_leaves))

RF comparison uses shared leaf labels and requires meaningful, preferably unique names. A zero maximum means no comparable splits; normalized RF is undefined (`None`), not evidence of agreement. Decide explicitly whether rooted or unrooted comparison is scientifically appropriate.

Detect duplication and speciation events

from ete4 import PhyloTree

gene_tree = PhyloTree(
    "((Hsa|g1,Ptr|g1),(Hsa|g2,M
Read more
@k-dense-ai
Ships withscientific-agent-skills

๐Ÿ”” Claude Scientific Skills is now Scientific Agent Skills. Same skills, broader compatibility โ€” now works with any AI agent that supports the open Agent Skills standard, not just Claude.

Stars on GitHub

Momentum

stars in total
55.6k
Star history of K-Dense-AI/scientific-agent-skills on GitHub, a chart by star-history.com

Other skills on scientific-agent-skills.

aeon

aeon

This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting,โ€ฆ

More skills from other plugins.

paddleocr-doc-parsing

paddleocr-doc-parsing

Use this skill to extract structured Markdown/JSON from PDFs and document imagesโ€”tables with cell-level precision, formulas asโ€ฆ

@paddlepaddle@paddlepaddleInstall Skill
context-loader
Auto-invoked

context-loader

Search memories from earlier Pi sessions in this repository. Use it when earlier work may already explain the code, error,โ€ฆ

mem04d69k
@mem0ai@mem0aiInstall Skill
analyzing-ai-citations

analyzing-ai-citations

Answer AI citation and answer engine optimization (AEO) questions in PostHog: whether AI answer engines (ChatGPT, Claude, and anโ€ฆ

posthog10d41k
@posthog@posthogInstall Skill
qmd

qmd

Search local markdown knowledge bases, notes, docs, and wikis with QMD. Use when users ask to find notes, retrieve documents,โ€ฆ

qmd3w31k
@tobi@tobiInstall Skill

Questions about etetoolkit.

Which coding agents can use etetoolkit?
etetoolkit installs in Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode and Windsurf with the skills CLI, using each agent's flag shown on this page. Flowy's auto-invocation, which fires a skill when your prompt matches, runs in Claude Code only.