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Refines broad, vague, or aspirational biomedical research objectives into clear, bounded, measurable, executable, and downstream-ready study objective statements. Always use this skill when a user has a general aim such as “explore a mechanism,” “study prognosis,” “investigate biomarkers,” or “look at treatment response,” but the objective is still too broad, non-operational, or too ambiguous to support protocol framing, design selection, analysis planning, or hypothesis design. Never assume that polished wording alone means the objective is actionable. Focus first on objective type, missing operational elements, scope discipline, and downstream-ready formulation.

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Build respawn-safe Roblox character systems around Players, CharacterAdded/CharacterRemoving, Humanoid, HumanoidRootPart, Animator, R6/R15 rigs, movement, animations and markers, death, tools, accessories, ownership, and custom characters. Use when character scripts break after respawn, cache stale Humanoids, control movement or velocity, load AnimationTracks, handle death, equip Tools, modify avatars, or support custom player rigs.

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Find and remove AI slop — the generic, machine-default visual and copy tics of vibe-coded products — from a web project. Use when the user asks to "kill AI slop", "de-slop", "remove the AI look", "make this not look AI-generated", or clean up a landing page / UI / docs that feels templated. Detects and fixes the catalogue of tells: indigo→violet gradients, gradient-clip headlines, the default semantic palette, one-hue status boxes, atmospheric gradients, serif-italic emphasis, highlighted keywords, AI copywriting voice ("not just X — it's Y"), emoji everywhere, glowing status dots, wobbling spinners, colored-left-border callouts, pastel icon tiles, glassmorphism, over-rounding, oversized shadows, borders that die at corners, badge & pill spam, AI-drawn SVG icons, kickers over every heading, flat type hierarchies, invented stat rows, 01/02/03 section markers, cards nested in cards, the default Inter/Space Grotesk look, and more. Works on HTML/CSS, React/Vue/Svelte/Astro, Tailwind, PHP, and Markdown copy.

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Transforms knowledge sources into an Obsidian StudyVault. Two modes: (1) Document Mode — PDF/text/web sources → study notes with practice questions. (2) Codebase Mode — source code project → onboarding vault for new developers. Mode is auto-detected based on project markers in CWD.

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Identify tumor neoantigens from somatic variants with pVACtools (pVACseq/pVACfuse/pVACbind/pVACvector/pVACview) for personalized cancer vaccines and checkpoint biomarkers. Encodes the field's hard truth that binding prediction is the easy, near-solved part and single-digit-percent PPV lives downstream — so it centers clonality/CCF, HLA LOH (the silent invalidator), expression, proximal-variant phasing, agretopicity/foreignness quality, and the predicted->presented->immunogenic validation tiers. Use when nominating vaccine targets, ranking neoantigens, or building a tumor-to-candidate pipeline. Binding details in mhc-binding-prediction; ranking in immunogenicity-scoring.

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Detects cancer and infers tissue-of-origin from cfDNA methylation by choosing conversion chemistry (bisulfite vs EM-seq vs TAPS vs cfMeDIP), calling read-level methylation haplotypes rather than averaged beta values, and deconvolving a hematopoietic-dominated cfDNA mixture against a methylation atlas via NNLS/quadratic programming. Encodes the GRAIL/CCGA thesis that thousands of tissue-specific markers make methylation outperform sparse mutations for multi-cancer early detection (MCED) and localization, and that single concordantly-methylated fragments give ppm-level sensitivity. Uses MethylDackel for extraction (mbias-then-extract), MEDIPS/QSEA for enrichment data, scipy.optimize.nnls for deconvolution. Use when building an MCED or methylation-MRD assay, picking a conversion chemistry for low-input plasma, or deconvolving tissue-of-origin from cfDNA.

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Implement, review, or improve maps and location features in iOS/macOS apps using MapKit and CoreLocation. Use when working with Map views, annotations, markers, polylines, user location tracking, geocoding, reverse geocoding, search/autocomplete, directions and routes, geofencing, region monitoring, CLLocationUpdate async streams, or location authorization flows. Also use when working with maps, coordinates, addresses, places, directions, distance calculations, or location-based features in Swift apps.

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Locate AST read/write usage markers and builtin CallOp usage rules in LuisaCompute. Use when investigating or modifying AST variable usage propagation, FunctionBuilder internals, or CallOp argument marking.

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Use when a Unity 6.3 task involves character animation or cameras: Mixamo or mocap humanoid import and retargeting, Animator Controllers, blend trees, layers and avatar masks, root motion, foot sliding, IK and Animation Rigging, Playables, Timeline cutscenes, custom tracks and markers, Cinemachine 3 cameras, camera jitter, flipping blends or cameras hitting walls; or when clips import with no animation, a character T-poses, an idle drifts, feet slide or the head misses its aim target.

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Use when turning a script or story into previs, layout, storyboards or an animatic in Blender: beats to shot list, camera and lens per shot, staging, camera height, 180-degree rule, screen direction, shot sizes, when to cut, camera moves, timing stills in the Video Sequencer, markers bound to cameras, Story Tools, Grease Pencil or 2D/3D hybrid boards. Also when an animatic shows the wrong frame, blocking keys are not stepped, Rigify operators are missing, or viewport render fails headless.

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Analyze images, video, speech, motion, products, and websites; route local vision, audio, depth, tracking, matting, identity, and restoration models; auto-edit, replicate, enhance, caption, voice, assemble, annotate, validate, and export editable Timeline Studio projects and videos. Use for reference-video remakes, filter and repeated-shot reconstruction, subject-aware reframing, clip splitting, source-time speed curves, Color Wheels grading, ramps and holds, person or product cutout, person or object outline, authorized face swap, shot and timing reconstruction, timeline markers, chapters, beat cues, review notes and ranges, supplied or web-sourced footage, AI video platform selection, cleanup, highlights, product promotion, website walkthroughs, image-to-video assisted edits, optical-flow editing, depth-assisted relighting, grayscale depth-video conversion, depth/2.5D/transition finishing, AI voiceover, subtitles, short-form production, .timeline automation, or editor evaluation.

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Generate tiered sentence frames for academic tasks that scaffold language production across proficiency levels. Use when EAL students need structured language support for classroom discourse.

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Expert blueprint for open world games including chunk-based streaming (load/unload regions dynamically), floating origin (prevent precision jitter beyond 5000 units), HLOD (hierarchical LOD for distant meshes), persistent state (track entity changes across unloaded chunks), POI discovery systems (compass, markers), and threaded loading (prevent stutters). Use for RPGs, sandboxes, or exploration games. Trigger keywords: open_world, chunk_streaming, floating_origin, HLOD, persistent_state, POI_discovery, threaded_loading.

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Drift detection + apply for a scaffolded harness. Re-renders the template with the same vars, computes added/removed/changed file plan, and applies with Git-style conflict markers or .rej files. Default is dry-run.

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Active credit card transfer bonuses from Amex, Chase, Capital One, Citi, Bilt, and Rove. Weekly-refreshed data with confidence markers. Use when pricing an award booking that involves a points transfer or deciding whether to wait for a better bonus.

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Resolve an in-progress Git merge or rebase conflict while preserving the relevant intent of both sides. Use when conflict markers or an interrupted merge/rebase need investigation and resolution.

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Loads full context for a React Flow (@xyflow/react) user journey mapping project. Use when working on, extending, debugging, or building features for the journey map tool. Triggers on: "journey map project", "open journey map", "work on journey map", "build user journey", "react flow journey project", "journey-map app", or any request to add features like swimlanes, emotion curves, persona nodes, touchpoints, or pain point markers.

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Interpret medical lab/test reports (blood panels, urine, liver/kidney function, thyroid, tumor markers, coagulation, cardiac enzymes, hormones, etc.) uploaded as images, PDFs, or text. Trigger whenever the user uploads a lab report, medical test result, or clinical diagnostic sheet — or says things like "help me read this report", "what do these results mean", "化验单", "检验报告", "帮我看看这个报告", "blood test results", "lab results", "体检报告", "检查报告单", "血常规", "尿常规", "肝功能", "肾功能", "甲功", "凝血", "interpret my labs", "are these results normal", "这些指标正常吗". Also trigger when the user uploads ANY medical-looking document with tables of values, reference ranges, or clinical test names — even if they don't explicitly ask for interpretation. Do NOT trigger for symptom triage (use emergency-triage instead), drug interaction queries, or general medical Q&A without an actual report to interpret.

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Create, modify, debug, or review Windows Forms applications only when the request contains a concrete Windows Forms marker. USE FOR: WinForms, Windows Forms, System.Windows.Forms, WinForms Form or UserControl designer files (*.Designer.cs or *.Designer.vb), Visual Studio WinForms Designer, TableLayoutPanel, BindingSource, DataGridView, Control.InvokeAsync, component-tray ownership, or custom control serialization. DO NOT USE FOR: WPF or WPF XAML, including Window.InputBindings, KeyBinding, commands, or DataContext; .NET MAUI; Avalonia; or any request where none of the listed Windows Forms markers is present.

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Run a single manual tmux-based QA scenario for the todo continuation feature against the real CLI (./pi-test.sh) in an interactive TUI. Captures scrollback, asserts deterministic pass/fail count markers, and cleans up test fixtures. Use only for the manual-qa milestone features.

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Track progress across work sessions using SESSION.md with git checkpoints and concrete next actions. Converts IMPLEMENTATION_PHASES.md into trackable session state with phase status, progress markers, and recovery points. Use when: starting projects after planning phase, resuming work after context clears, managing multi-phase implementations, or troubleshooting lost context, missing progress tracking, or unclear next steps.

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scRNA-seq with Scanpy: QC, normalization, HVG selection, PCA, neighborhood graph, UMAP/t-SNE, Leiden clustering, markers, cell annotation, trajectory inference. Standard scRNA-seq exploration.

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Cell type annotation strategy for scRNA-seq: name clusters manually from canonical markers, transfer labels from a reference (CellTypist, popV), or do both and validate one against the other. Covers matching tissue and developmental stage, marker evidence, annotation confidence, doublets, unresolved clusters. Use when planning or troubleshooting how to annotate cells.

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Guide for annotating statistical significance (p-value asterisks) on comparison plots. Covers standard notation (ns, *, **, ***, ****), matplotlib bracket+asterisk implementation, and use with seaborn box/violin/bar plots. Use when preparing publication-ready figures with significance markers.

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