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 agentmods add skills/aristoteleo/pantheonos/bio_image_processingnpx skills add aristoteleo/PantheonOS --skill bio_image_processinggit clone --depth 1 https://github.com/aristoteleo/PantheonOSWrote 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/aristoteleo/pantheonos/bio_image_processing)<a href="https://agentmods.dev/skills/aristoteleo/pantheonos/bio_image_processing"><img src="https://agentmods.dev/badge/skills/aristoteleo/pantheonos/bio_image_processing.svg" alt="Measured on agentmods" 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 | $0.00025 | $0.00354 |
| Opus 5 | $0.00013 | $0.00177 |
| Sonnet 5 | $0.00005 | $0.00071 |
| Haiku 4.5 | $0.00003 | $0.00035 |
Grade A, and why
Bio Image Processing Skills Index 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 6d 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.
What it actually says
Agent Skills for Biological Image Processing
Best practices and workflows for biological image analysis tasks including cell segmentation, image restoration, and spatial data processing. Load the relevant skill files when performing specific analysis tasks.
Cell & Nucleus Segmentation
Tools and workflows for instance segmentation of cells and nuclei in microscopy images. Covers deep-learning methods (Cellpose, SAM-based, StarDist) with guidance on model selection, GPU/CPU inference, fine-tuning, and 3D segmentation.
Skill index: segmentation/SKILL.md
Skills:
- Cellpose: General-purpose cell/nucleus segmentation (Cellpose 3, Cellpose-SAM)
- SAM-Based Methods: CellSAM, micro-sam, SAMCell for automatic and interactive segmentation
When to use:
- Segmenting cells or nuclei in fluorescence, brightfield, or phase contrast images
- Need instance masks from 2D or 3D microscopy data
- Comparing or selecting between segmentation tools for your imaging modality
- Fine-tuning a segmentation model on custom training data
Using Skills
- Before analysis: Scan this index for relevant skills
- Load skill file: Read the full skill document for detailed guidance
- Follow best practices: Use the code snippets and workflows provided
- Adapt as needed: Skills are templates; adjust for your specific data
What ships with it
6 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.
- 6d ago First seen · 43 lines · 25 tokens per session scan A bc3591bda72c
Bio Image Processing Skills Index is a skill published in the GitHub repository aristoteleo/PantheonOS (482 stars, last pushed 3d ago), licensed BSD-2-Clause. It adds 25 tokens to every session and 354 once invoked, about $0.0001 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 2026-08-30.
Other skills, from other repositories
sn-search-academic
用于学术调研、论文精读、相关工作梳理、百科知识查询和引用链追溯。.
paper-revision-author
Revise independently drafted paper sections into one coherent LaTeX body before the abstract is written.
imaging-data-commons
Query and download public cancer imaging data from NCI Imaging Data Commons using idc-index. Use for accessing large-scale radiology (CT, MR, PET) and pathology datasets for AI training or research. No authentication required. Query by metadata, visualize in browser, check licenses.
clinical-decision-support
Generate professional clinical decision support (CDS) documents for pharmaceutical and clinical research settings, including patient cohort analyses (biomarker-stratified with outcomes) and treatment recommendation reports (evidence-based guidelines with decision algorithms). Supports GRADE evidence grading…
molecular-cloning
Molecular cloning simulation and design. PCR amplicon prediction, restriction enzyme digestion, Golden Gate and Gibson assembly simulation, primer design, CRISPR sgRNA design, and plasmid annotation. For protein-level sequence analysis use biopython or esm; for database lookups use gene-database or ensembl-database.
geo-database
Access NCBI GEO for gene expression/genomics data. Search/download microarray and RNA-seq datasets (GSE, GSM, GPL), retrieve SOFT/Matrix files, for transcriptomics and expression analysis.