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 agentlas-ai/agentlas-desktop --skill ggetgit clone --depth 1 https://github.com/agentlas-ai/agentlas-desktopWrote 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/agentlas-ai/agentlas-desktop/gget)<a href="https://agentmods.dev/skills/agentlas-ai/agentlas-desktop/gget"><img src="https://agentmods.dev/badge/skills/agentlas-ai/agentlas-desktop/gget/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/agentlas-ai/agentlas-desktop/gget"><img src="https://agentmods.dev/badge/skills/agentlas-ai/agentlas-desktop/gget.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 | $0.00093 | $0.02048 |
| Opus 5.5 | $0.00037 | $0.00819 |
| Sonnet 5.5 | $0.00019 | $0.00410 |
| Haiku 4.5 | $0.00009 | $0.00205 |
Grade A, and why
gget 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 gget — 89 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 — 171 lines — stays where its author put it; the contents beside it link to each section on GitHub.
gget
Overview
gget is a command-line bioinformatics tool and Python package providing unified access to 20+ genomic databases and analysis methods. Query gene information, sequence analysis, protein structures, viral sequences, expression data, disease associations, and mouse tissue/cell specificity metrics through a consistent interface. Most gget modules work both as command-line tools and as Python functions.
Important: The databases queried by gget are continuously updated, which sometimes changes their structure. Guidance here targets gget 0.30.5 (PyPI current as of 2026-06-07). For reproducible work, pin gget==0.30.5; for broken upstream database adapters, update gget after checking release notes.
Installation
Install gget in a clean virtual environment to avoid conflicts:
# Reproducible install targeting this skill
uv venv .venv
source .venv/bin/activate
uv pip install "gget==0.30.5"
# In Python/Jupyter
import gget
Quick Start
Basic usage pattern for all modules:
# Command-line
gget <module> [arguments] [options]
# Python
gget.module(arguments, options)
Most modules return:
- Command-line: JSON (default) or CSV with
-csvflag - Python: DataFrame or dictionary
Common flags across modules:
-o/--out: Save results to file-q/--quiet: Suppress progress information-csv: Return CSV format (command-line only)
Python argument names generally match long CLI options without leading dashes. For example, --census_version becomes census_version=.... Use gget <module> --help for the exact current signature.
Module Categories
gget exposes 23 modules in six categories. Parameters, CLI and Python examples, and return shapes for every one are in references/module_catalog.md; fuller per-parameter documentation is in references/module_reference.md.
| Category | Modules |
|---|---|
| 1. Reference & gene information | ref (Ensembl reference downloads), search (gene search), info (gene/transcript detail), seq (nucleotide and protein sequences) |
| 2. Sequence analysis & alignment | blast, blat, muscle (multiple alignment), diamond (local alignment) |
| 3. Structural & protein analysis | pdb (structures and metadata), alphafold (structure prediction), elm (linear motifs) |
| 4. Expression & disease data | archs4 (correlation, tissue expression), cellxgene (single-cell), enrichr (enrichment), bgee (orthology and expression), opentargets (disease and drug), cbio (cancer genomics), cosmic (mutations) |
| 5. Viral & mouse specificity | virus (viral sequences), 8cube (mouse specificity and expression) |
| 6. Additional tools | mutate (mutated sequences), gpt (text generation), setup (install module dependencies) |
What ships with it
8 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.
- references/common_workflows.md 3.1 KB
- references/database_info.md 12 KB
- references/module_catalog.md 23 KB
- references/module_reference.md 21 KB
- references/workflows.md 25 KB
- scripts/batch_sequence_analysis.py 6.0 KB runs code
- scripts/enrichment_pipeline.py 7.0 KB runs code
- scripts/gene_analysis.py 6.1 KB runs code
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 · 171 lines · 93 tokens per session scan A 00d58845fd2f
gget is a skill published in the GitHub repository agentlas-ai/agentlas-desktop (6 stars, last pushed yesterday), licensed Apache-2.0. It adds 93 tokens to every session and 2,048 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 94% identical to gget, differing in 89 lines, and is treated as a copy.
Other skills, from other repositories
tbtools
Use when the user asks about TBtools, TBtools-II, TBtools RPC API, TBtools CLI, or bioinformatics operations available through TBtools such as sequence manipulation, BLAST, GFF/GTF/GXF processing, expression tables, heatmaps, trees, MCScanX, DIAMOND, HMMER, MUSCLE, and IQ-TREE.
electron-expert
Expert in Electron framework, desktop app development, IPC, and cross-platform packaging. Use when the user mentions desktop, Node.js, cross platform, Windows, macOS, or Linux, or when the task involves Electron Architecture, Process Types, IPC Communication, or App Lifecycle.
research-orchestrator
Becomes a principal research scientist who orchestrates deep, multi-source research by coordinating evidence gathering, grading source quality, and synthesizing findings with explicit confidence levels. Use when the user needs a comprehensive research report on a complex topic, evidence-based analysis with source…
autoresearch
Run an auto research / autoresearch loop for measurable improvements. Use when optimizing a skill, agent, prompt, code path, benchmark, or other target with a mechanical metric: baseline, mutate one thing, verify, keep or discard, log, chart progress, and optionally save improved custom skills or agents through Open…
architecture-diagram
How to draw and maintain the architecture diagram Ensemblr keeps for a workspace — ensemblrgetarchitecturediagram to fetch the stored one (it answers with null when nobody has drawn this workspace yet), the IR shape, how to derive it from the codebase, and ensemblrupdatearchitecturediagram to store it. Read this when…
scaffold-lean-library
Scaffold a Lean 4 library with Mathlib or PFR, Lake tests, and CI. Use for "new Lean project"; to edit Lean, use write-lean-code.