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 magic3007/dotfiles --skill latchbio-integrationgit clone --depth 1 https://github.com/magic3007/dotfilesWrote 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/magic3007/dotfiles/latchbio-integration)<a href="https://agentmods.dev/skills/magic3007/dotfiles/latchbio-integration"><img src="https://agentmods.dev/badge/skills/magic3007/dotfiles/latchbio-integration/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/magic3007/dotfiles/latchbio-integration"><img src="https://agentmods.dev/badge/skills/magic3007/dotfiles/latchbio-integration.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 | $0.00045 | $0.02281 |
| Opus 5.5 | $0.00018 | $0.00912 |
| Sonnet 5.5 | $0.00009 | $0.00456 |
| Haiku 4.5 | $0.00005 | $0.00228 |
Grade A, and why
latchbio-integration 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 1mo 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.
This is a copy
94% identical to latchbio-integration — 12 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 353 lines — stays where its author put it; the contents beside it link to each section on GitHub.
LatchBio Integration
Overview
Latch is a Python framework for building and deploying bioinformatics workflows as serverless pipelines. Built on Flyte, create workflows with @workflow/@task decorators, manage cloud data with LatchFile/LatchDir, configure resources, and integrate Nextflow/Snakemake pipelines.
Core Capabilities
The Latch platform provides four main areas of functionality:
1. Workflow Creation and Deployment
- Define serverless workflows using Python decorators
- Support for native Python, Nextflow, and Snakemake pipelines
- Automatic containerization with Docker
- Auto-generated no-code user interfaces
- Version control and reproducibility
2. Data Management
- Cloud storage abstractions (LatchFile, LatchDir)
- Structured data organization with Registry (Projects → Tables → Records)
- Type-safe data operations with links and enums
- Automatic file transfer between local and cloud
- Glob pattern matching for file selection
3. Resource Configuration
- Pre-configured task decorators (@small_task, @large_task, @small_gpu_task, @large_gpu_task)
- Custom resource specifications (CPU, memory, GPU, storage)
- GPU support (K80, V100, A100)
- Timeout and storage configuration
- Cost optimization strategies
4. Verified Workflows
- Production-ready pre-built pipelines
- Bulk RNA-seq, DESeq2, pathway analysis
- AlphaFold and ColabFold for protein structure prediction
- Single-cell tools (ArchR, scVelo, emptyDropsR)
- CRISPR analysis, phylogenetics, and more
Quick Start
Installation and Setup
# Install Latch SDK
uv pip install latch
# Login to Latch
latch login
# Initialize a new workflow
latch init my-workflow
# Register workflow to platform
latch register my-workflow
Prerequisites:
- Docker installed and running
- Latch account credentials
- Python 3.8+
Basic Workflow Example
from latch import workflow, small_task
from latch.types import LatchFile
@small_task
def process_file(input_file: LatchFile) -> LatchFile:
"""Process a single file"""
# Processing logic
return output_file
@workflow
def my_workflow(input_file: LatchFile) -> LatchFile:
"""
My bioinformatics workflow
Args:
input_file: Input data file
"""
return process_file(input_file=input_file)
What ships with it
4 files 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.
- 1mo ago First seen · 353 lines · 45 tokens per session scan A 8d657e91a917
latchbio-integration is a skill published in the GitHub repository magic3007/dotfiles (11 stars, last pushed yesterday), licensed MIT. It adds 45 tokens to every session and 2,281 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 94% identical to latchbio-integration, differing in 12 lines, and is treated as a copy.
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