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 get-available-resourcesgit 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/get-available-resources)<a href="https://agentmods.dev/skills/k-dense-ai/scientific-agent-skills/get-available-resources"><img src="https://agentmods.dev/badge/skills/k-dense-ai/scientific-agent-skills/get-available-resources/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/get-available-resources"><img src="https://agentmods.dev/badge/skills/k-dense-ai/scientific-agent-skills/get-available-resources.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 | $0.00063 | $0.02278 |
| Opus 5 | $0.00032 | $0.01139 |
| Sonnet 5 | $0.00013 | $0.00456 |
| Haiku 4.5 | $0.00006 | $0.00228 |
Grade A, and why
get-available-resources 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 8d 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.
How it starts
The opening of the file, as written. The whole thing — 278 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Get Available Resources
Build a conservative picture of resources available to the current process. Keep host inventory, process affinity, cgroup/container limits, scheduler allocation, and accelerator runtime usability separate.
Safety contract
Follow these rules:
- Run detection when the user requests it or a specific workload needs resource planning. Do not persist a fingerprint for every scientific task.
- Use stdout by default. Persist only when the user chooses an explicit generic local filename.
- Do not run stress tests, benchmarks, large allocations, write probes, device resets, driver installation, or clock/power changes.
- Do not dump the environment. Read only the named Slurm and accelerator variables implemented by the detector.
- Do not report hostnames, absolute paths, cgroup paths, job IDs, device UUIDs, PCI addresses, or raw visibility-variable values.
- Treat a missing observation as unknown. Never convert unknown to unlimited.
- Never infer that a visible host CPU, memory pool, or GPU is usable inside a scheduler allocation or container.
The bundled detector uses only fixed executable/argument tuples, no shell, short timeouts, bounded stdout/stderr, and partial-failure warnings.
Quick start
Run from this skill directory.
Ephemeral stdout snapshot
python scripts/detect_resources.py
The command emits only JSON to stdout. Redirect it only when ordinary shell permissions are acceptable.
Explicit private file
python scripts/detect_resources.py --output resource-snapshot.json
Explicit output is restricted to one .json filename in the current
directory, uses private permissions, rejects symlinks and path traversal, and
refuses overwrite unless --force is supplied.
Optional psutil enhancement
The standard-library detector works without installation. For broader cross-platform physical-core, affinity, available-memory, swap, and disk coverage:
uv pip install "psutil==7.2.2"
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/resource_semantics.md 9.0 KB
- references/snapshot_schema.md 5.5 KB
- references/sources.md 7.1 KB
- scripts/_common.py 5.9 KB runs code
- scripts/accelerator_diagnostics.py 4.5 KB runs code
- scripts/detect_resources.py 58 KB runs code
- scripts/plan_workload.py 11 KB runs code
- scripts/snapshot_tools.py 17 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.
- 8d ago Changed · +17 lines 1ecca3aff630
- 12d ago First seen · 261 lines · 63 tokens per session scan A f9d65a3a81ff
get-available-resources is a skill published in the GitHub repository K-Dense-AI/scientific-agent-skills (44,220 stars, last pushed 4d ago), licensed MIT. It adds 63 tokens to every session and 2,278 once invoked, about $0.0003 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
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…
inbound-lead-enrichment
Fills in missing data for inbound leads — researches the company, identifies the person's role and seniority, finds other stakeholders at the company, checks for existing CRM relationships, and updates the lead record. Produces enriched lead data ready for qualification or outreach. Tool-agnostic.
demo-builder
Builds personalized demo assets for top prospects using the founder's product API/MCP/SDK. Researches prospect, proposes demo concepts, builds working prototype, tests it, and generates comparison report with live demo link.
create-imessage-mockup
Render pixel-accurate iMessage screenshot mockups (DM or group) from a thread JSON. Supports minimal, with-keyboard, and full iPhone 15 Pro frame variants. Outputs HTML + PNG.
industry-scanner
Daily industry intelligence scanner. Scans web, social media, news, blogs, and communities for industry-relevant events, trends, and signals. Produces a comprehensive intelligence briefing plus strategic GTM opportunity ideas. Orchestrates existing scraping skills — does not reimplement data collection.