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Scientific Computing

Browse agent skills for scientific simulations, computational research, and data science

Categories, GitHub stars, and source recency help organize and order the catalog. These signals are not an endorsement, quality certification, safety review, or guarantee of fit. Open a skill detail and inspect its source before use.

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9,484 results

hugging-science

SourceK-Dense-AI/scientific-agent-skills/skills/hugging-science/SKILL.md
Updated

Discovers and evaluates scientific datasets, models, methodology posts, and Spaces through the Hugging Science catalog. Used when selecting scientific ML resources in biology, chemistry, genomics, materials, climate, physics, astronomy, medicine, mathematics, protein design, single-cell analysis, or PDE modeling, and when checking their actual datasets, Transformers, native-runtime, Inference Providers, or Gradio interfaces.

marine-carbonate-chemistry

SourceK-Dense-AI/scientific-agent-skills/skills/marine-carbonate-chemistry/SKILL.md
Updated

Solves seawater carbonate chemistry with PyCO2SYS for chemical oceanography, ocean acidification, and marine carbon-cycle research. Use for paired total alkalinity, dissolved inorganic carbon, pH, or seawater pCO2/fCO2 measurements; carbonate speciation; aragonite and calcite saturation; Revelle factors; lab-to-in-situ temperature and pressure corrections; and measurement uncertainty propagation. Applies to carbonate-system calculations, not general aqueous speciation or air-sea gas-flux estimation.

detecting-stuxnet-style-attacks

Sourcemukul975/Anthropic-Cybersecurity-Skills/skills/detecting-stuxnet-style-attacks/SKILL.md
Updated

Detects sophisticated cyber-physical attacks that follow the Stuxnet pattern of modifying PLC logic while spoofing sensor readings to hide the manipulation, using PLC logic integrity monitoring (Claroty xDome, Nozomi Guardian) and physics-based process anomaly detection. Use when hunting for IT-to-OT lateral movement or discrepancies between PLC program state and physical process behavior in ICS/SCADA environments.

detecting-t1055-process-injection-with-sysmon

Sourcemukul975/Anthropic-Cybersecurity-Skills/skills/detecting-t1055-process-injection-with-sysmon/SKILL.md
Updated

Detect process injection techniques (T1055) - including DLL injection, process hollowing, and APC injection - by analyzing Sysmon Event IDs 1, 7, 8, 10, and 25 for cross-process memory operations, remote thread creation, and anomalous DLL loads. Use when hunting defense-evasion activity that hides code inside legitimate processes, investigating an EDR alert on suspicious cross-process access, or validating Sysmon coverage for injection detection.

exploratory-data-analysis

Sourcedavila7/claude-code-templates/cli-tool/components/skills/scientific/exploratory-data-analysis/SKILL.md
Updated

Perform comprehensive exploratory data analysis on scientific data files across 200+ file formats. This skill should be used when analyzing any scientific data file to understand its structure, content, quality, and characteristics. Automatically detects file type and generates detailed markdown reports with format-specific analysis, quality metrics, and downstream analysis recommendations. Covers chemistry, bioinformatics, microscopy, spectroscopy, proteomics, metabolomics, and general scientific data formats.

neurokit2

Sourcedavila7/claude-code-templates/cli-tool/components/skills/scientific/neurokit2/SKILL.md
Updated

Comprehensive biosignal processing toolkit for analyzing physiological data including ECG, EEG, EDA, RSP, PPG, EMG, and EOG signals. Use this skill when processing cardiovascular signals, brain activity, electrodermal responses, respiratory patterns, muscle activity, or eye movements. Applicable for heart rate variability analysis, event-related potentials, complexity measures, autonomic nervous system assessment, psychophysiology research, and multi-modal physiological signal integration.

pyopenms

Sourcedavila7/claude-code-templates/cli-tool/components/skills/scientific/pyopenms/SKILL.md
Updated

Python interface to OpenMS for mass spectrometry data analysis. Use for LC-MS/MS proteomics and metabolomics workflows including file handling (mzML, mzXML, mzTab, FASTA, pepXML, protXML, mzIdentML), signal processing, feature detection, peptide identification, and quantitative analysis. Apply when working with mass spectrometry data, analyzing proteomics experiments, or processing metabolomics datasets.

mujoco-python

Sourcegoogle-deepmind/mujoco/doc/skills/python/SKILL.md
Updated

Python simulation lifecycle (MjSpec, MjModel, MjData), simulation stepping (mj_step, mj_step1, mj_step2, mj_forward), named access (data.body, model.geom), bind(), multi-threaded CPU batch simulation (mujoco.batch.Batch, mujoco.rollout), optimization and system ID (mujoco.minimize, mujoco.sysid, mjd_transitionFD), contact and touch sensors, sensordata, keyframe resets, integrators, mju_ spatial math (quaternions, poses), energy diagnostics. Use for Python physics simulation, state access, CPU batching, stepping loops, sensors. Do NOT use for model building/editing (mujoco-spec-editing), headless rendering (mujoco-rendering), GPU/TPU (mujoco-accelerated), cross-engine parity debugging (mujoco-parity), or GUI/viewers (mujoco-gui, mujoco-studio).

exploratory-data-analysis

SourcezLanqing/codex-claude-academic-skills/scientific-toolkit-skill/references/scientific-skills/exploratory-data-analysis/SKILL.md
Updated

Perform comprehensive exploratory data analysis on scientific data files across 200+ file formats. This skill should be used when analyzing any scientific data file to understand its structure, content, quality, and characteristics. Automatically detects file type and generates detailed markdown reports with format-specific analysis, quality metrics, and downstream analysis recommendations. Covers chemistry, bioinformatics, microscopy, spectroscopy, proteomics, metabolomics, and general scientific data formats.