Media Claude Skills
3 032 media skills from 496 authors. They create and process images, video and sound. Half of them fit into 1 962 tokens or less — that is what one costs your context window when the agent loads it. 771 ship runnable scripts rather than instructions alone. 30 of them cannot work without an MCP server, most often rube. We also found 347 copies of these same skills sitting in other people's repositories — counted once here, not 347 times.
3 032 unique 496 authors 13 updated this month 173 from vendors
Preprocesses photographed sheets of many business cards — slicing each into overlapping high-resolution tiles and de-glaring them with container tooling (OpenCV/ImageMagick) — then reads every card via cheap parallel temperature-0 API calls (Haiku or Sonnet) using a distilled extraction prompt, and writes deduped contact fields to a CSV. Use when a user has photos or scans holding multiple business cards per image, mentions glare or unreadable cards, batch card transcription, contact extraction, or wants to read many cards without an expensive in-conversation pass. Triggers on 'business cards', 'card scan', 'extract contacts', 'read these cards', 'card glare', 'too many cards per photo'.
Portrait Mode for SVGs — foveated vectorization with 4-zone selective detail. Combines vision annotations, MediaPipe segmentation/landmarks, and optional saliency. Like phone portrait mode, but vectorized. Use when vectorizing a portrait or photo where subject detail should outrank background detail.
Sort grocery lists by aisle order using store aisle sign photos. Build aisle maps from uploaded images, match items to aisles, and output optimized shopping routes. Use when users upload aisle sign photos, request grocery list sorting, want shopping trip optimization, need store layout mapping, or mention grocery list organization.
Create mathematical animations with Manim Community Edition(manimce). Generates distinctive, production-grade animations that avoid generic "AI slop" aesthetics. Use when user wants to animate concepts, equations, illustrate proofs, visualize algorithms, create math explainers, or produce 3Blue1Brown-style videos.
ACTIVATE when drafting all-hands speeches, investor updates, quarterly letters to stakeholders, press statements, CEO announcements, crisis communications, customer updates, or any mission-critical communication to employees, investors, customers, or media. Executive communications require persuasion, clarity, emotional intelligence, and alignment with company values and strategy.
> "draw an architecture diagram", "帮我画个对比图", "visualize this process", "make a diagram for this doc", or mentions 流程图/架构图/示意图/对比图/时序图/泳道图/时间线. Also trigger when user provides a document/article and asks for illustrations or diagrams. or artistic image requests (logos, mascots, drawings of objects/people — those need an image tool).
> AgentCall (agentcall.dev) — Join a video meeting (Google Meet, Teams, Zoom) as an AI bot with voice and visual presence. Supports audio-only mode with voice intelligence (barge-in, interruptions), text-to-speech mode, and webpage modes for custom UI. Use when asked to join a call, attend a meeting, or participate in a video conference.
Convert raster figures into high-fidelity editable SVG and native PowerPoint packages. Use for screenshots, paper figures, workflow diagrams, architecture diagrams, infographics, UI schematics, charts/maps, posters, covers, and image-heavy technical figures when labels, formulas, structure, source-specific assets, and complex continuous backgrounds must be reconstructed with useful editability.
Review SDS-PAGE or protein purification gel images using DNA sequence, protein sequence, base-pair length, expected protein size, and lane labels. Use when the user wants to judge whether a gel ran well, whether the main band matches the expected product, or whether there may be impurities, degradation, aggregation, or low expression.
Cell segmentation from multiplexed tissue images. Covers deep learning (Cellpose, Mesmer) and classical approaches for nuclear and whole-cell segmentation. Use when extracting single-cell data from IMC or MIBI images after preprocessing.
Load and preprocess imaging mass cytometry (IMC) and MIBI data. Covers MCD/TIFF handling, hot pixel removal, and image normalization. Use when starting IMC analysis from raw MCD files or preparing images for segmentation.
Process and analyze tissue images from spatial transcriptomics data using Squidpy. Extract image features, segment cells/nuclei, and compute morphological features from H&E or IF images. Use when processing tissue images for spatial transcriptomics.
Visualize spatial transcriptomics data using Squidpy and Scanpy. Create tissue plots with gene expression, clusters, and annotations overlaid on histology images. Use when visualizing spatial expression patterns.
Draw and export phylogenetic trees using Biopython Bio.Phylo with matplotlib and modern alternatives. Use when creating tree figures, customizing colors and labels, exporting to image formats, or choosing between Bio.Phylo, ggtree, ETE4, and iTOL for publication.
Set up a compute environment on a remote provider so Claude Science jobs can run there. Covers direct SSH/conda hosts, Slurm clusters, container-via-bridge runners, and managed-API providers (Modal, GCP, RunPod). Use when standing up a new provider, porting an env to a different backend, adding a tool that needs its own software stack, or wiring weight caches. Triggers on "new compute provider", "set up env on", "port env to", "build GPU image", "weight cache", "compute_details", "conda env on the box", "apptainer on slurm".
Run GPU jobs on the user's own Modal account via host.compute.create('byoc:modal', ...). Covers the create→submit→wait_for_notification flow, the compute_provider kernel for env setup, image/volume resolution, and the two approval cards. Load once you've decided to dispatch to Modal.
Cell segmentation in fluorescence microscopy images. Supports Cellpose/cpsam (Cellpose 4.0) with additional backends planned. Produces segmentation masks, per-cell morphology metrics (area, diameter, centroid, eccentricity), overlay figures, and a report.md.
Medication photo to personalised PGx dosage card via Claude vision — snap a pill, get genotype-informed guidance
Generate professional presentation slides and high-quality illustrations using Gemini image generation API (Nano Banana 2), with interactive browser-based review and iterative editing. Full workflow: content planning conversation → slides_plan.json → batch image generation → review with feedback → targeted slide editing → PPTX packaging. Use when: user wants to create a presentation, make slides, generate a PPT/PPTX, prepare a talk deck, design visual slide content, or generate high-quality figures/illustrations for papers and documents. Do NOT use for: writing academic papers (use paper-writing) or planning academic conference talk narrative structure (use academic-slides).
Extract cognitive patterns and thinking fingerprints from any text. Use this skill when the user wants to analyze how someone thinks, understand cognitive style, profile writing or speech patterns, compare thinking styles between people, asks "what's my thinking style", "analyze how this person reasons", "cognitive profile", "thinking pattern", "DHDNA", "digital DNA", or wants to understand the mind behind any text. Also trigger when the user provides text and wants deeper insight into the author's reasoning patterns, decision-making style, or cognitive signature.
Generate or edit images using AI models (FLUX, Nano Banana 2). Use for general-purpose image generation including photos, illustrations, artwork, visual assets, concept art, and any image that is not a technical diagram or schematic. For flowcharts, circuits, pathways, and technical diagrams, use the scientific-schematics skill instead.
Lightweight WSI tile extraction and preprocessing. Use for basic slide processing tissue detection, tile extraction, stain normalization for H&E images. Best for simple pipelines, dataset preparation, quick tile-based analysis. For advanced spatial proteomics, multiplexed imaging, or deep learning pipelines use pathml.
Microscopy data management platform. Access images via Python, retrieve datasets, analyze pixels, manage ROIs/annotations, batch processing, for high-content screening and microscopy workflows.
Self-hosted, open-source alternative to Google NotebookLM for AI-powered research and document analysis. Use when organizing research materials into notebooks, ingesting diverse content sources (PDFs, videos, audio, web pages, Office documents), generating AI-powered notes and summaries, creating multi-speaker podcasts from research, chatting with documents using context-aware AI, searching across materials with full-text and vector search, or running custom content transformations. Supports 16+ AI providers including OpenAI, Anthropic, Google, Ollama, Groq, and Mistral with complete data privacy through self-hosting.
Python library for working with DICOM (Digital Imaging and Communications in Medicine) files. Use this skill when reading, writing, or modifying medical imaging data in DICOM format, extracting pixel data from medical images (CT, MRI, X-ray, ultrasound), anonymizing DICOM files, working with DICOM metadata and tags, converting DICOM images to other formats, handling compressed DICOM data, or processing medical imaging datasets. Applies to tasks involving medical image analysis, PACS systems, radiology workflows, and healthcare imaging applications.
This skill should be used when working with pre-trained transformer models for natural language processing, computer vision, audio, or multimodal tasks. Use for text generation, classification, question answering, translation, summarization, image classification, object detection, speech recognition, and fine-tuning models on custom datasets.
Automated cell behavior analysis from microscopy or XR lab recordings. Classifies cell motion phenotypes (migration, proliferation, apoptosis, division, quiescence), computes population-level quantitative metrics (growth rate, migration velocity, directionality index), and emits structured JSON for downstream reporting, plotting, or ELN integration.
Detects common wet-lab procedural and safety errors from XR or fixed-camera lab video. Identifies pipette volume deviations, forgotten reagent additions, uncapped tubes, contamination risks, sample mix-ups, and other observable hazards. Outputs structured JSON with error type, timestamp, severity, and corrective action suggestions for real-time alerts or post-hoc audit.
Converts first-person XR headset video into a structured experiment timeline log. Extracts timestamped events (action, object, location, result) via VLM or action recognition, outputs Markdown or JSON for downstream analysis, reporting, protocol compliance audit, or ELN attachment.
Egocentric Hand-Object Segmentation (EgoHOS) - pixel-level hand and object segmentation in egocentric videos. Outputs fine-grained segmentation masks with hand regions highlighted. Specialized for hand-object interaction scenarios with pixel-accurate masks. Ideal for detailed interaction analysis.
General-purpose experimental data extractor from lab video streams. Ingests footage from XR headsets or fixed cameras and extracts typed, timestamped measurements — liquid volume levels, color/turbidity shifts, cell and colony counts, pipette readouts, instrument display values, gel band intensities — emitting a time-series JSON or CSV table ready for downstream analysis, charting, or ELN attachment.
Generates natural language scene descriptions from 3D Gaussian Splatting reconstructions built from lab photos or short video clips. Outputs structured text with instrument placement, sample positions, spatial layout keywords, and relational predicates — optimized for VLM or spatial intelligence model consumption in protocol guidance, error detection, or AR overlay generation.
Automated SCI-standard Methods section generator from experiment execution records. Parses LabOS skill call chains, structured JSON logs (extract_experiment_data_from_video, analyze_lab_video_cell_behavior), protocol text, and ELN entries to produce flowing, past-tense, passive-voice Methods prose with full reagent citations, equipment model numbers, and statistical analysis subsections. Outputs LaTeX (\subsection{} / \paragraph{}) or Markdown, ready for direct insertion into a manuscript draft.
High-quality 3D hand pose estimation for egocentric videos from ECCV 2024 (ap229997/hands). Provides 3D joint keypoints and skeleton visualization projected to 2D. Optimized for daily egocentric activities with state-of-the-art accuracy. Outputs hand skeleton overlays on video frames.
HOT3D (Hand-Object 3D Dataset) by Meta Facebook - multi-view egocentric hand and object 3D tracking for Aria/Quest smart glasses. State-of-the-art multi-view 3D hand pose, object pose, and hand-object interaction tracking. Supports visualization with 3D joint projections, meshes, and skeletal overlays on video frames.
Real-time XR video vs. protocol text matching and deviation detection. Aligns first-person XR headset video streams frame-by-frame against structured protocol steps, flags procedural deviations, scores compliance, and delivers corrective audio/visual overlays — enabling one-person lab operation with zero-missed-step guarantees.
Generates short, imperative guidance prompts for the next experimental step from current video frame and protocol context. Output is optimized for voice broadcast (TTS) or AR overlay — concise, actionable, command-style — to guide researchers in real time, correct deviations, or resume experiments without breaking flow.
Maps natural language voice commands to concrete LabClaw skill invocations. Parses ASR output, identifies intent, selects target skill, fills parameters from context, and provides prompt templates — enabling hands-free, voice-driven anywhere-lab experiences where researchers control analysis, guidance, and data export by speaking.
Use this skill whenever the user wants an end-to-end workflow for the BOLD5000 dataset, including download, BIDS organization, and processing of task-fMRI data with visual image stimuli. Triggers include: 'BOLD5000', 'BOLD 5000', 'process BOLD5000', 'visual fMRI', or any request to run the BOLD5000 pipeline. This is the NeuroClaw dataset-orchestration layer for BOLD5000.
Use this skill whenever the user wants an end-to-end workflow for the IXI (Information eXtraction from Images) dataset, including data download, BIDS organization, and multimodal processing of T1w, T2w, and MRA. Triggers include: 'IXI', 'IXI dataset', 'process IXI data', 'IXI MRI', or any request to run the IXI multimodal pipeline.
Use this skill whenever NeuroClaw needs concrete nibabel operations for neuroimaging files: loading and validating NIfTI images, inspecting shapes and affine matrices, saving derived images, converting voxel coordinates to MNI/world coordinates, or reading FreeSurfer geometry and annotation files. Triggers include: 'nibabel', 'inspect NIfTI', 'read affine', 'save nifti', 'voxel to MNI', 'atlas coordinates', 'read FreeSurfer surface', 'read annot', or any request focused on low-level neuroimaging I/O rather than full preprocessing.
Use this skill whenever the user wants to perform automated white matter hyperintensity (WMH) segmentation on structural MRI data using the MARS-WMH nnU-Net model. Requires one FLAIR and one T1w NIfTI image (no contrast). Triggers include: 'wmh', 'white matter hyperintensities', 'WMH segmentation', 'MARS-WMH', 'wmh-nnunet', 'segment FLAIR T1', 'white matter lesions', 'vascular WMH', 'mars wmh', or any request to run nnU-Net WMH segmentation on FLAIR+T1w pair.
Production-ready microscopy image analysis and quantitative imaging data skill for colony morphometry, cell counting, fluorescence quantification, and statistical analysis of imaging-derived measurements. Processes ImageJ/CellProfiler output (area, circularity, intensity, cell counts), performs Dunnett's test, Cohen's d effect size, power analysis, Shapiro-Wilk normality tests, two-way ANOVA, polynomial regression, natural spline regression with confidence intervals, and comparative morphometry. Supports CSV/TSV measurement tables, multi-channel fluorescence data, colony swarming assays, and neuron counting datasets. Use when analyzing microscopy measurement data, colony area/circularity, cell count statistics, swarming assays, co-culture ratio optimization, or answering questions about imaging-derived quantitative data.
| image restoration, and spatial data processing.
| Cell and nucleus segmentation tools for microscopy images. Covers Cellpose, SAM-based methods, StarDist, InstanSeg, and Mesmer.
Clawd 像素风动画生成器。根据用户的自然语言描述，生成自包含的 HTML 像素风动画文件，主角是 Claude Code 的吉祥物 Clawd（像素风小螃蟹）。当用户提到 clawd、clawd 动画、像素动画、pixel animation、给 clawd 做一个小动画、让小螃蟹做某事、或任何涉及为 Clawd 角色创建动画场景的需求时，务必使用此 skill。即使用户只是说"让小螃蟹安慰一下我"或"今天和小螃蟹的合作很愉快"，也应触发。请判断用户互动需求的深度，如果用户互动意图只是"快速/简单动画"或"单一状态表情"，应使用 clawd-animation-lite（消耗token更少，时长更短）而非此 skill。
协助意疏写「意疏的AI口袋」公众号文章。Claude 是协作者不是写手——voice 必须从意疏嘴里出来，AI 负责结构化、扩写、降 AI 味。触发：写公众号文章 / 帮我整理口述 / 有素材但想不清 / 这段 AI 味太重 / 看看有没有意疏味道 / 帮我把骨架写成文章。输出 Markdown，排版找 wechat-formatter，发布找 wechat-publisher。