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Found 1,783 Skills
Read-only Storage Analysis Assistant for macOS / Windows (auto-detects system). Scans the entire disk usage to identify space hogs, categorizes each item into three levels: 🟢 Auto-cleanable / 🟡 Manual judgment required / 🔴 Clean with caution, and provides actionable disposal plans. Generates an interactive HTML report with beautiful formatting, collapsible sections, and one-click copy commands. Also supports starting a local service to delete files directly via the web (move to trash / delete immediately). The entire scanning process is read-only. Must be used in the following scenarios: When users mention "storage analysis", "disk full", "C drive/hard disk full", "insufficient space", "clean up space", "disk cleanup", "space occupied", "what's taking up space", "help me check storage", "check computer storage/space", "storage space", "computer space insufficient", "memory full/insufficient" (in Chinese colloquial, "memory" often refers to storage), "storage analysis", "disk cleanup", "clear cache", "disk cleanup"; or when users complain about insufficient computer space, want to know what's taking up hard disk space, or need cleanup suggestions. Note: If users explicitly refer to RAM (e.g., "which process is using memory", "high memory usage", want to see Activity Monitor), that's RAM, not storage, and does not belong to this skill.
Production recipes for GSAP SVG animations. Companion to official gsap-plugins skill (API reference). Triggers: SVG animation, GSAP SVG, path drawing, strokeDashoffset, DrawSVG, drawSVG, SVG morph, MorphSVGPlugin, circuit tree, circuit board, CTAHud, HUD animation, pulse ring, scallop wave, SVG stagger, SVG fill, SVG stroke, SVG cleanup, feGaussianBlur, SVG glow, SVG blink, shape overlay, page transition, section transition, smooth morph, morph interpolation, dynamic morphing, SVG curtain, shape transition. Non-triggers: Not for text animation (use gsap-text), scroll reveals without SVG (use gsap-scroll), mouse interactions (use gsap-interact), or non-SVG visual effects (use gsap-vfx). Outcome: Produces SVG animations — path drawing, morphing, circuit board patterns, HUD systems, pulse rings, and scallop waves.
Use when designing, executing, or facilitating a complete SWOT strategic analysis workflow — especially when the task involves environment scanning (PEST/industry analysis), competitive positioning, S/W/O/T identification and validation, strategy formulation via SO/ST/WO/WT collision, and strategy selection. Trigger on requests such as SWOT analysis, strengths and weaknesses analysis, opportunities and threats analysis, strategy positioning, external environment analysis, competitive strategy, TOWS Matrix, SWOT to strategy, PEST analysis, or any combination of competitive analysis and strategy direction. Also trigger when the user uploads a case, company description, or product brief and asks for strategic analysis or positioning.
Security scanner and health check for your AI agent skills tree. Identifies dead skills, missing documentation, and unsafe shell execution paths.
Pre-migration readiness assessor for porting NumPy to cuPyNumeric. Use BEFORE substantial porting work begins when the user asks whether code will scale on GPU, whether they should migrate to cuPyNumeric, which NumPy patterns transfer cleanly, what must be refactored before porting, or mentions pre-port assessment, scaling analysis, or refactor planning. Inspect the user's source code, look up NumPy usage, cross-reference the cuPyNumeric API support manifest, and distinguish distributed-scaling-friendly patterns from blockers such as unsupported APIs, scalar synchronization, host round-trips, Python/object-heavy control flow, shape/data-dependent branching, and in-place mutation hazards. Produce a verdict of READY, LIGHT REFACTOR, SIGNIFICANT REFACTOR, or NOT RECOMMENDED, with concrete refactor pointers.
Workflow required before any Mule flow and integration work. Call use_skill as your FIRST action — before reading project files — whenever the user asks to create, generate, update, fix, modify, change, edit, tweak, adjust, or rework any Mule flow, sub-flow, or component. Do not read project files and attempt the change yourself — even targeted single-component changes like 'modify the choice router', 'fix the until-successful', or 'update the catch block' require this workflow. Covers all change types, new integrations and targeted changes to error handlers, catch blocks, choice routers, DataWeave transforms, HTTP listeners, foreach loops, retry policies, scatter-gathers, connectors, and variable assignments. Prompts beginning with 'This code defines...' or 'This flow...' are generation requests, not analysis. When you call this skill, it must be the only tool call in that response.
Use when operating the vigolium CLI for web vulnerability scanning, security testing, traffic ingestion, server management, AI agent-driven scanning and code review, cloud-storage management, or writing custom JavaScript extensions. Invoke for scan commands, scan-url, scan-request, run, ingest, server, agent (query/autopilot/swarm/olium/piolium/audit/session), traffic browsing, database queries, storage uploads/downloads, module management, extension scripting, export, project management, and configuration tuning.
Efficient storage and retrieval of genomic variant data using TileDB. Scalable VCF/BCF ingestion, incremental sample addition, compressed storage, parallel queries, and export capabilities for population genomics.
RNA velocity analysis with scVelo. Estimate cell state transitions from unspliced/spliced mRNA dynamics, infer trajectory directions, compute latent time, and identify driver genes in single-cell RNA-seq data. Complements Scanpy/scVI-tools for trajectory inference.
Decide where files live in an ML experimentation project: reusable code in `src/<pkg>/`, one `# %%` script per experiment in `experiments/`, design notes + index in `journal/`, reports in `reports/`, agent-only probes in `scratch/`, narrative digest in `overview/summary.md`. Owns the layout, the file-creation rules (one file per experiment, ask before editing), and the jupytext `# %%` script convention. Never imposes `data/` — the user owns that. TRIGGER — any of: - Starting a new ML project / scaffolding a workspace. - About to create the first experiment file in a project. - About to create `src/<pkg>/data.py` / `features.py` / `pipeline.py` / `evaluate.py` for the first time. - About to write a `.ipynb` for experimentation — redirect to a `# %%` script under `experiments/`. - User asks where something should live, how to organize the project, or how to set up the workspace. - About to add a new experiment iteration — decide new file vs edit existing (ask the user). SKIP when: the file is clearly part of an already-populated module (e.g., adding a function to existing `features.py`); pure refactor inside a single existing file; pipeline declaration mechanics (`build-ml-pipeline`); evaluation mechanics (`evaluate-ml-pipeline`); skore symbol lookup (`python-api`). HOW TO USE: **first run the Detection table** below — if any signal matches, glue to existing conventions (do not rename or move folders). If no signal matches, scaffold the default layout. **Emit the Pre-flight checklist as visible text and read the Stop conditions before any file is created or edited.** Use templates in `templates/`; copy and adapt, do not rewrite from scratch.
Rank outreach campaigns by real revenue impact — which campaigns actually generated deals, pipeline, or meetings — by cross-referencing the user's La Growth Machine campaign data with their CRM deal data (HubSpot today). Use whenever the user wants to know which campaigns drove pipeline, compare campaign ROI, see which campaigns to continue / stop / adapt, audit campaign impact, review attribution, asks 'which of my campaigns is actually working', or wants a campaign performance ranking by deals or revenue. Triggers on: 'which campaigns drove pipeline', 'rank my campaigns by deals', 'campaign ROI', 'campaign impact', 'which campaigns to stop', 'which to scale', 'attribution review', 'pipeline by campaign'. Pulls live data from the La Growth Machine MCP and the HubSpot MCP when connected; works from pasted exports otherwise. For RevOps, Heads of Sales/Marketing, founders and growth leads doing campaign performance reviews. Maintained by La Growth Machine.
Use when creating a new Elastic integration package, scaffolding data streams, answering package layout or structure questions, or running the end-to-end integration build workflow. Covers package topology, scaffold commands, post-scaffold edits, and full orchestration of CEL/pipeline/test subagents.