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Found 516 Skills
Launch the Fava web UI for visual exploration of your Beancount ledger. Interactive charts, account views, queries, and reports in the browser. Use when you want to visually explore your financial data. CLEAR step: R (Report)
Create a PRD through user interview, codebase exploration, and module design, then submit as a GitHub issue. Use when user wants to write a PRD, create a product requirements document, or plan a new feature.
Explore a codebase for architectural friction, discover refactoring opportunities, and propose module-deepening refactors as GitHub issue RFCs. Uses friction-driven exploration and parallel sub-agents to design multiple interface alternatives. Use when user wants to improve architecture, find refactoring opportunities, consolidate coupled modules, reduce complexity, make code more testable, or review codebase health.
Build identity-preserving character generation workflows and pipelines in ComfyUI. Selects the optimal identity method (InfiniteYou, FLUX Kontext, PuLID, InstantID, IP-Adapter) based on use case requirements. Handles face preservation, likeness transfer, cross-domain conversion (3D to photo), multi-reference consistency, iterative character editing, and character variation generation. Triggers on requests to generate consistent characters, preserve identity across images, create face-swapping workflows, or convert 3D renders to photorealistic portraits. Does NOT cover general image generation without identity preservation, model training/LoRA fine-tuning, animation, technical explanations, or workflow debugging.
This skill should be used when finding, tracing, or understanding code in a repository with SymDex available. Trigger it for requests like "where is this defined?", "who calls this?", "what route handles this path?", "show me the file outline", "search this codebase by intent", or any task that would otherwise rely on broad Read/Grep/Glob exploration.
Generative ideation engine. Takes a domain, trend, question, or constraint and produces 15-30 novel possibilities — things that might be true, businesses that could exist, futures that could unfold. Spawns a team of 6 specialist agents — Signal Scout, Analogist, Inverter, Combinator, Contrarian, Futurist — who each generate ideas from a distinct creative angle. The lead cross-pollinates across agents, finds unexpected combinations, and ranks the output by novelty × plausibility. Use when the user says "brainstorm", "what could exist", "what's possible", "generate ideas", "what might be true", "possibilities", or presents a domain and wants divergent exploration rather than evaluation of a specific idea.
Conversational bug discovery → issue draft. Light listening, background exploration, scope assessment. Asks before gh issue create — never auto-files. Use when conducting a QA session, triaging user-reported issues, or filing bugs.
Apply PyGraphistry graph ML/AI workflows such as UMAP, DBSCAN, embedding-based anomaly analysis, and fit/transform pipelines on nodes or edges. Use for feature-driven exploration, clustering, anomaly triage, and graph-AI notebook workflows.
Search and analyze cryo-EM maps, single particle structures, tomography datasets, and raw micrograph data from EMDB, EMPIAR, and CryoET Data Portal. Cross-reference with PDB structures and AlphaFold predictions. Use for cryo-EM map discovery, structure fitting analysis, raw data access, and tomography exploration.
Write raw ClickHouse SQL for a SigNoz dashboard panel — timeseries, value, or table widgets that the builder UI cannot express (custom joins, window functions, regex extraction over log bodies, aggregations beyond builder syntax). Trigger when the user explicitly asks for a "ClickHouse query", a "raw SQL panel", a "custom SQL widget", or describes a SigNoz dashboard panel whose query needs SQL the builder cannot produce. Anchored to dashboard-panel SQL specifically. For ad-hoc data exploration that does not need to land in a panel, use `signoz-generating-queries` instead.
Transform static system design diagrams into interactive, explorable visualizations using AI-powered analysis and React Flow.
L2 AI-driven web UI testing for a React/Vite dashboard app. Originally authored against the Onsager Dashboard (the body's route table + file paths are Onsager-shaped); other React dashboards fork the procedure and substitute their own routes / test paths. Use when testing UI on PRs, triaging L1 test failures, or verifying UI behavior at desktop + mobile viewports. Triggers include "test the UI", "check the dashboard", "triage L1 failure", "run L2 tests", "validate this PR", "exploratory test the web app".