Scientific Agent Skills is a collection of reusable procedures that give AI agents capabilities for scientific research across areas such as biology, chemistry, medicine, and drug discovery. It is used by researchers and by people building AI scientist workflows with compatible coding agents. The catalogue contains many of the project's skills and supporting instructions.
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 K-Dense-AI/scientific-agent-skills --skill depmapgit clone --depth 1 https://github.com/K-Dense-AI/scientific-agent-skillsWrote 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/k-dense-ai/scientific-agent-skills/depmap)<a href="https://agentmods.dev/skills/k-dense-ai/scientific-agent-skills/depmap"><img src="https://agentmods.dev/badge/skills/k-dense-ai/scientific-agent-skills/depmap/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/k-dense-ai/scientific-agent-skills/depmap"><img src="https://agentmods.dev/badge/skills/k-dense-ai/scientific-agent-skills/depmap.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- NVIDIA SkillSpector pass
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 | $0.00052 | $0.02709 |
| Opus 5 | $0.00026 | $0.01354 |
| Sonnet 5 | $0.00010 | $0.00542 |
| Haiku 4.5 | $0.00005 | $0.00271 |
Grade A, and why
depmap scanned grade A with 1 finding 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 11d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
response = requests.get(url, params=params) Copies of this mod
7 near-identical copies found in the catalogue:
How it starts
The opening of the file, as written. The whole thing — 302 lines — stays where its author put it; the contents beside it link to each section on GitHub.
DepMap — Cancer Dependency Map
Overview
The Cancer Dependency Map (DepMap) project, run by the Broad Institute, systematically characterizes genetic dependencies across hundreds of cancer cell lines using genome-wide CRISPR knockout screens (DepMap CRISPR), RNA interference (RNAi), and compound sensitivity assays (PRISM). DepMap data is essential for:
- Identifying which genes are essential for specific cancer types
- Finding cancer-selective dependencies (therapeutic targets)
- Validating oncology drug targets
- Discovering synthetic lethal interactions
Key resources:
- DepMap Portal: https://depmap.org/portal/
- DepMap data downloads: https://depmap.org/portal/download/all/
- Python package:
depmap(or access via API/downloads) - API: https://depmap.org/portal/api/
When to Use This Skill
Use DepMap when:
- Target validation: Is a gene essential for survival in cancer cell lines with a specific mutation (e.g., KRAS-mutant)?
- Biomarker discovery: What genomic features predict sensitivity to knockout of a gene?
- Synthetic lethality: Find genes that are selectively essential when another gene is mutated/deleted
- Drug sensitivity: What cell line features predict response to a compound?
- Pan-cancer essentiality: Is a gene broadly essential across all cancer types (bad target) or selectively essential?
- Correlation analysis: Which pairs of genes have correlated dependency profiles (co-essentiality)?
Core Concepts
Dependency Scores
| Score | Range | Meaning |
|---|---|---|
| Chronos (CRISPR) | ~ -3 to 0+ | More negative = more essential. Common essential threshold: −1. Pan-essential genes ~−1 to −2 |
| RNAi DEMETER2 | ~ -3 to 0+ | Similar scale to Chronos |
| Gene Effect | normalized | Normalized Chronos; −1 = median effect of common essential genes |
Key thresholds:
- Chronos ≤ −0.5: likely dependent
- Chronos ≤ −1: strongly dependent (common essential range)
Cell Line Annotations
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.
- 11d ago First seen · 302 lines · 52 tokens per session scan A 39ed3b4766ca
depmap is a skill published in the GitHub repository K-Dense-AI/scientific-agent-skills (44,220 stars, last pushed 3d ago), licensed MIT. It adds 52 tokens to every session and 2,709 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
discovery-toolbox
A routed repertoire of 90 scientific thinking operators for biological research agents - visual reasoning, detectability and information budgets, search reframing, causal identification, competing explanations, observation and selection processes, pipeline artifact diagnosis, effort allocation, and confirmation…
discovery-director
Operate as a research director making original discoveries from a given biological question and dataset. Use when the task is open-ended scientific research, exploring omics or experimental data for findings, hypothesis generation and testing, screening a large candidate space of genes, variants, features or…
polars-dovmed
Search PMC Open Access and bioRxiv corpora with polars-dovmed. Use when structured, reproducible literature queries should run through the hosted API or local parquet indexes.
bio-interdomain-hgt
Detect and polarize interdomain horizontal gene transfer with homology, context, and phylogenetic checks. Use when studying lateral gene transfer, virus-host gene exchange, endogenous viral elements, or donor direction.
csag-extraction
Extract a Conditional Scientific Argumentation Graph and grounded Q&A from a manuscript. Use when representing assertions, contexts, evidence links, and inference steps in machine-readable form.
notebooks
Author, execute, validate, and convert reproducible marimo or Jupyter notebooks. Use when delivering an analysis notebook with all cells run and figures embedded.