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 qutipgit 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/qutip)<a href="https://agentmods.dev/skills/k-dense-ai/scientific-agent-skills/qutip"><img src="https://agentmods.dev/badge/skills/k-dense-ai/scientific-agent-skills/qutip/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/qutip"><img src="https://agentmods.dev/badge/skills/k-dense-ai/scientific-agent-skills/qutip.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 | $0.00055 | $0.03761 |
| Opus 5 | $0.00028 | $0.01880 |
| Sonnet 5 | $0.00011 | $0.00752 |
| Haiku 4.5 | $0.00006 | $0.00376 |
Grade A, and why
qutip 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 — 335 lines — stays where its author put it; the contents beside it link to each section on GitHub.
QuTiP 5
Scope
Use QuTiP for finite-dimensional quantum mechanics, quantum optics, Lindblad dynamics, trajectories, weak-coupling Bloch-Redfield models, and specialized Floquet, HEOM, and permutational-invariance methods. It is not a hardware execution SDK. Circuit and control functionality moved to separate QuTiP family packages.
This skill targets QuTiP 5.3.0, released 2026-05-22. QuTiP 5.3 requires
Python 3.11 or newer. Its required distributions are NumPy (>=1.23.2), SciPy
(>=1.9.2, excluding 1.16.0 and 1.17.0), and packaging.
Reproducible uv snapshot
Create a dedicated environment and pin every direct distribution:
uv venv --python 3.11
uv pip install "qutip==5.3.0"
For plots:
uv pip install "qutip[graphics]==5.3.0"
Optional QuTiP family packages are independently versioned:
uv pip install "qutip-qip==0.4.2"
uv pip install "qutip-qtrl==0.2.0"
uv pip install "qutip-jax==0.1.1"
qutip-qip0.4.2 (2026-06-23) is the production/stable circuit, gate, and noisy-device simulation package. Import fromqutip_qip, notqutip.qip.qutip-qtrl0.2.0 (2026-06-23) provides GRAPE and CRAB quantum optimal control. It is not a trajectory viewer. Import fromqutip_qtrl, notqutip.control; PyPI still classifies it pre-alpha.qutip-jax0.1.1 (2025-05-29) is the official JAX data backend for GPU and automatic-differentiation experiments. It is explicitly pre-alpha.qutip-cupyis an official QuTiP-organization repository, but it has no PyPI release and its own README says it is not officially released. Do not put an unreleased Git install into a reproducible workflow.
Use a project lockfile or a hash-generating uv pip compile workflow when
transitive dependency identity must also be frozen.
Non-negotiable model contract
Before solving, record:
- Units and convention. QuTiP equations normally set (\hbar=1). Hamiltonian entries are angular frequencies and rates have reciprocal-time units. Convert cyclic frequency with (2\pi f); never mix Hz and rad/s.
- Subsystem order.
tensor(A, B, C)fixes subsystem indices0, 1, 2. Preserve that order in every state, operator, collapse channel, and partial trace.obj.ptrace([0, 2])keeps those subsystems; it does not trace them. - State validity. Check ket norm or density-matrix Hermiticity, unit trace, and eigenvalues above a stated negative tolerance. Tiny negative values may be numerical; material negativity invalidates a claimed state.
- Generator meaning. A Lindblad channel with rate
gammais represented bysqrt(gamma) * A, notgamma * A. Define what each rate measures. For example,sqrt(gamma_phi / 2) * sigmaz()gives coherence decayexp(-gamma_phi * t). - Approximations. State rotating-wave, Born-Markov, secular, weak-coupling, bath-equilibrium, truncation, symmetry, and initial-factorization assumptions wherever used.
- Numerics. Justify Hilbert truncation, output grid, integration method,
tolerances, trajectory count, and random seeds. Report
result.stats. - Convergence. Sweep every artificial cutoff: Fock dimension, time/frequency window and spacing, ODE tolerances, trajectories, Floquet harmonics, HEOM depth and bath exponents, or PIQS representation as applicable.
What ships with it
12 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/advanced.md 13 KB
- references/analysis.md 10 KB
- references/core_concepts.md 8.3 KB
- references/time_evolution.md 12 KB
- references/visualization.md 8.6 KB
- scripts/_common.py 12 KB runs code
- scripts/convergence_sweep.py 12 KB runs code
- scripts/qobj_model_validator.py 11 KB runs code
- scripts/result_audit.py 12 KB runs code
- scripts/solver_config_planner.py 9.9 KB runs code
- scripts/steady_state_spectrum_planner.py 7.8 KB runs code
- scripts/two_level_simulation.py 12 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 First seen · 335 lines · 55 tokens per session scan A df46feb9e92c
qutip 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 55 tokens to every session and 3,761 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 2026-09-03.
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…
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.
exploratory-data-analysis
Inspect scientific data and generate a Markdown structure-and-quality report. Use when triaging tabular, array, sequence, HDF5, JSON, or raster files before downstream analysis.