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 tamarindgit 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/tamarind)<a href="https://agentmods.dev/skills/k-dense-ai/scientific-agent-skills/tamarind"><img src="https://agentmods.dev/badge/skills/k-dense-ai/scientific-agent-skills/tamarind/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/tamarind"><img src="https://agentmods.dev/badge/skills/k-dense-ai/scientific-agent-skills/tamarind.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- NVIDIA SkillSpector warn
SkillSpector: 4 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Data Exfiltration · line 120 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 136 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 221 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Excessive Agency · line 266 Skill allows unbounded resource consumption (API calls, storage, compute). Without rate limits or quotas, a compromised or misbehaving agent can cause denial-of-service or cost overruns.Fix: Set explicit rate limits, timeouts, and resource quotas for API calls, file operations, and compute. Implement circuit breakers for runaway loops.
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 | $0.00174 | $0.03137 |
| Opus 5.5 | $0.00070 | $0.01255 |
| Sonnet 5.5 | $0.00035 | $0.00627 |
| Haiku 4.5 | $0.00017 | $0.00314 |
Grade A, and why
tamarind 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 25d 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.
curl --fail-with-body 'https://app.tamarind.bio/tools.json?type=alphafold' How it starts
The opening of the file, as written. The whole thing — 211 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Tamarind Bio
Tamarind runs molecular-design and structural-biology tools on managed compute: structure prediction, protein and antibody design, docking, binding-affinity prediction, MSA generation, and molecular dynamics. Use it when the user requests Tamarind, its REST API/MCP server, or cloud execution of these scientific tools. For local sequence processing or molecular descriptors, use a local library.
Sources and review scope
The REST contracts and public catalog were reviewed on 2026-09-30. Examples are illustrative until validated against the user's account; this review did not run authenticated jobs or establish scientific accuracy for any model.
- API index and complete guide.
- Current OpenAPI includes discovery, validation, jobs, files, and newer pipeline/custom-tool surfaces. openapi.yaml is also available. Check that needed paths exist: the merged spec can return HTTP 200 with only its classic surface when the backend spec cannot be fetched.
- Public catalog needs no key; query
?type=or?tag=. It documents public tools and conditional required settings, not every optional parameter or account entitlement. - Product documentation index links to Markdown pages, including the MCP guide.
Fetch the account's current schemas before composing a run. Where the prose guide and OpenAPI differ, prefer the operation/schema for field shapes, and record any unresolved difference rather than guessing.
Access
- Use the user's Tamarind deployment. The shared base is
https://app.tamarind.bio/api; a dedicated organization deployment has its own host and account data. Every relative REST path below is under/api. - Obtain a key from the deployment's API settings and read it from
TAMARIND_API_KEY; send it asx-api-key. Keep keys out of files and logs. - Check the account's current allowance and compute budget before scaling up. Free usage is a monthly allowance, not an unconditional promise of ten jobs forever; billing and entitlements can change.
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.
- 25d ago Changed · -75 lines · +2 tokens per session aa9bb0aa10ac
- 26d ago Changed 5e95c6638302
- 1mo ago First seen · 286 lines · 172 tokens per session scan A 05332a8580d1
tamarind is a skill published in the GitHub repository K-Dense-AI/scientific-agent-skills (54,777 stars, last pushed yesterday), licensed MIT. It adds 174 tokens to every session and 3,137 once invoked, about $0.0007 per session on Opus 5.5. 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 2026-09-03.
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…
bio-interdomain-hgt
Detect and polarize interdomain horizontal gene transfer with reciprocal hits, genomic context, and gene trees. Use for virus-host gene exchange, endogenous viral elements, or donor direction.
scholion
Second-opinion support for individuals and clinicians, one person's data at a time — genome, laboratory history, prescriptions, wearables. It reads them locally and states what the data cannot support. No data is baked into the skill: everyone supplies their own. Use it when you need to check a physician's…
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, run and convert marimo or Jupyter notebooks. Use when delivering an analysis notebook executed end to end with figures embedded.