Etetoolkit

What it does

When your agent uses it

• Tasks that involve Bioinformatics
• Tasks that involve Accounting and bookkeeping

Example prompts

• “/etetoolkit”

Requirements

• Python 3
• Compatibility (from SKILL.md): 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].
• Pre-approved tools (allowed-tools): Read, Write, Edit, Bash, Python

Workflow steps

7 steps, taken from the first numbered list in SKILL.md.

1. 1Confirm the parser preserves the intended internal names, support, and
2. 2Check for empty and duplicate leaf names before name-based lookup or RF
3. 3State whether the tree is treated as rooted or unrooted.
4. 4Preserve branch lengths when pruning only if retained pairwise distances
5. 5Treat arbitrary polytomy resolution as a display/algorithmic convenience,
6. 6Record ETE version, parser, rooting method, pruning set, and taxonomy
7. 7Prefer iterators for large trees and get_cached_content() for repeated

What it can do on your machine

Read from SKILL.md and the folder at commit 92ace75. It shows what the files ask for, not the result of running them.

• Tool permissions

  Pre-approves these tools, so the agent can use them without asking each time:

  • Read
  • Write
  • Edit
  • Bash
  • Python

  From allowed-tools in the SKILL.md frontmatter.

• Runs code

  Ships 2 files in scripts/ (Python), which the agent can run.

  Shell commands in SKILL.md call:

  • uv

  From the folder's file list and the shell code blocks in SKILL.md.

• Network

  Hosts in commands or code, which the agent is likely to contact:

  • etetoolkit.github.io

  Also links to:

  • github.com
  • arxiv.org
  • pypi.org
  • doi.org
  • export.arxiv.org

  From URLs in SKILL.md, links to its own repository left out.

• Credentials

  Names no API keys, tokens, secrets or passwords.

  From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

• 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].

  From compatibility in the SKILL.md frontmatter.

Context cost

Etetoolkit loads about 3.3k tokens when it runs, and up to ~21k if it reads all its reference files. Until then it costs about 115 tokens; SKILL.md has 970 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it

~115

When it runs · the whole SKILL.md, loaded when a task matches

~3.3k

With references · SKILL.md plus every file in references/, read only if the agent opens them

~21k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

• NotePre-approves every shell command (allowed-tools: Bash)SKILL.md

  allowed-tools: Read, Write, Edit, Bash, Python

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from K-Dense-AI/scientific-agent-skills at commit 92ace75, republished under its GPL-3.0-or-later licence (© K-Dense-AI). 970 words, ~3,318 tokens.

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.

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].

license

GPL-3.0-or-later

metadata.version

3.0

metadata.last-reviewed

2026-09-30

metadata.skill-author

K-Dense Inc.

uv pip install "ete4==4.4.0"

# 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"

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

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"],
)

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,
)

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))

from ete4 import PhyloTree

gene_tree = PhyloTree(
    "((Hsa|g1,Ptr|g1),(Hsa|g2,Mmu|g1));",
    sp_naming_function=lambda name: name.split("|", 1)[0],
)

for event in gene_tree.get_descendant_evol_events(sos_thr=0.0):
    relationship = "speciation/orthology" if event.etype == "S" else "duplication/paralogy"
    print(relationship, sorted(event.in_seqs), sorted(event.out_seqs))

from ete4 import NCBITaxa

ncbi = NCBITaxa()
names = ["Homo sapiens", "Pan troglodytes", "Mus musculus"]
name_to_taxids = ncbi.get_name_translator(names)

unresolved = {
    name: name_to_taxids.get(name, [])
    for name in names if len(name_to_taxids.get(name, [])) != 1
}
if unresolved:
    raise ValueError(f"Names need NCBI taxonomy disambiguation: {unresolved}")

taxids = [name_to_taxids[name][0] for name in names]
taxonomy_tree = ncbi.get_topology(taxids)
print(taxonomy_tree.to_str(props=["sci_name", "rank"]))

from ete4 import Tree

tree = Tree("((A:1,B:1)90:0.2,C:1);", parser="support")
tree.explore()

tree.render_sm("tree.png", w=1200, h=800)

uv run --no-project --isolated --with "ete4==4.4.0" python scripts/tree_operations.py \
  stats tree.nw --parser 1
uv run --no-project --isolated --with "ete4==4.4.0" python scripts/tree_operations.py \
  ascii tree.nw --parser 1 --props name,dist
uv run --no-project --isolated --with "ete4==4.4.0" python scripts/tree_operations.py \
  convert tree.nw output.nw \
  --input-parser 1 --output-parser 1
uv run --no-project --isolated --with "ete4==4.4.0" python scripts/tree_operations.py \
  reroot tree.nw rooted.nw \
  --parser 1 --midpoint
uv run --no-project --isolated --with "ete4==4.4.0" python scripts/tree_operations.py \
  prune tree.nw pruned.nw \
  --parser 1 --keep species1 species2 species3
uv run --no-project --isolated --with "ete4==4.4.0" python scripts/tree_operations.py \
  compare tree_a.nw tree_b.nw

# Interactive SmartView
uv run --no-project --isolated --with "ete4==4.4.0" python scripts/quick_visualize.py \
  tree.nw --parser 1

# SmartView PNG (requires ete4[render-sm])
uv run --no-project --isolated --with "ete4[render-sm]==4.4.0" python scripts/quick_visualize.py \
  tree.nw tree.png \
  --parser support --mode circular --show-support --color-by-support --support-scale percent

# Vector output via Qt treeview (requires ete4[treeview])
uv run --no-project --isolated --with "ete4[treeview]==4.4.0" python scripts/quick_visualize.py \
  tree.nw tree.svg \
  --parser 1 --engine treeview --title "Species phylogeny"

© K-Dense-AI, GPL-3.0-or-later. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 8 other files (scripts, references) in skills/etetoolkit of K-Dense-AI/scientific-agent-skills.

• SKILL.md
• references/api_reference.md
• references/migration-ete3-to-ete4.md
• references/review.md
• references/taxonomy.md
• references/visualization.md
• references/workflows.md
• scripts/quick_visualize.py
• scripts/tree_operations.py

Open the folder on GitHubat commit 92ace75

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in K-Dense-AI/scientific-agent-skills, which our catalogue first saw on October 7, 2026.

• lingxling/awesome-skills-cnclaude-scientific-skills/skills/etetoolkit