Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add thesecondfox/skill --skill bio-epidemiological-genomics-phylodynamicsgit clone --depth 1 https://github.com/thesecondfox/skillWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/thesecondfox/skill/bio-epidemiological-genomics-phylodynamics)<a href="https://agentmods.dev/skills/thesecondfox/skill/bio-epidemiological-genomics-phylodynamics"><img src="https://agentmods.dev/badge/skills/thesecondfox/skill/bio-epidemiological-genomics-phylodynamics/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/thesecondfox/skill/bio-epidemiological-genomics-phylodynamics"><img src="https://agentmods.dev/badge/skills/thesecondfox/skill/bio-epidemiological-genomics-phylodynamics.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00064 | $0.01732 |
| Opus 5 | $0.00032 | $0.00866 |
| Sonnet 5 | $0.00013 | $0.00346 |
| Haiku 4.5 | $0.00006 | $0.00173 |
Grade A, and why
bio-epidemiological-genomics-phylodynamics scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 208 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Version Compatibility
Reference examples tested with: BioPython 1.83+, TreeTime 0.11+, scanpy 1.10+
Before using code patterns, verify installed versions match. If versions differ:
- Python:
pip show <package>thenhelp(module.function)to check signatures - CLI:
<tool> --versionthen<tool> --helpto confirm flags
If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying.
Phylodynamics
"Build a time-scaled tree for my outbreak" → Estimate divergence times and molecular clock rates from dated sequences to reconstruct outbreak timing and evolutionary dynamics.
- Python:
treetime.TreeTime()for maximum likelihood time-scaled trees - CLI:
treetime --tree tree.nwk --aln aln.fasta --dates dates.tsv
TreeTime Basic Usage
from treetime import TreeTime
from Bio import Phylo
# Load tree and alignment
tree = Phylo.read('tree.nwk', 'newick')
# Create TreeTime object with dates
# dates_file: tab-separated with columns 'name' and 'date'
# Date formats: 2020.5, 2020-06-15, numeric (decimal year)
tt = TreeTime(
tree=tree,
aln='alignment.fasta',
dates='dates.tsv',
gtr='JC69' # Nucleotide model: JC69, HKY85, GTR
)
# Run molecular clock analysis
tt.run(
root='best', # Root optimization: 'best', 'least-squares', or clade name
Tc='skyline', # Coalescent prior: None, 'skyline', 'opt', or numeric
time_marginal='assign_ml' # Date estimation method
)
# Access results
print(f'Root date: {tt.tree.root.numdate:.2f}')
print(f'Clock rate: {tt.clock_rate:.2e} subs/site/year')
TreeTime CLI
# Install treetime
pip install phylo-treetime
# Basic time tree
treetime --tree tree.nwk --aln alignment.fasta --dates dates.tsv --outdir results/
# With coalescent prior (for population dynamics)
treetime --tree tree.nwk --aln alignment.fasta --dates dates.tsv \
--coalescent skyline --outdir results/
# Ancestral sequence reconstruction
treetime ancestral --tree tree.nwk --aln alignment.fasta --outdir results/
# Mugration (discrete trait analysis, e.g., geographic spread)
treetime mugration --tree tree.nwk --states locations.tsv \
--attribute location --outdir results/
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 10d ago First seen · 208 lines · 64 tokens per session scan A 87772e91d1a2
bio-epidemiological-genomics-phylodynamics is a skill published in the GitHub repository thesecondfox/skill (3 stars, last pushed 5mo ago), licensed MIT. It adds 64 tokens to every session and 1,732 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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