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Found 160 Skills
Construct and analyze compound-target-disease networks for drug repurposing, polypharmacology discovery, and systems pharmacology. Builds multi-layer networks from ChEMBL, OpenTargets, STRING, DrugBank, Reactome, FAERS, and 60+ other ToolUniverse tools. Calculates Network Pharmacology Scores (0-100), identifies repurposing candidates, predicts mechanisms, and analyzes polypharmacology. Use when users ask about drug repurposing via network analysis, multi-target drug effects, compound-target-disease networks, systems pharmacology, or polypharmacology.
Investigate a cluster of GitHub issues and PRs, determine canonical candidates, post duplicate/related status, preserve contributor credit, and execute cleanup actions (comments, closes, labels, changelog touchpoints).
CI-only self-improvement workflow using gh-aw (GitHub Agentic Workflows). Captures recurring failure patterns and quality signals from pull request checks, emits structured learning candidates, and proposes durable prevention rules without interactive prompts. Use when: you want automated learning capture in CI/headless pipelines.
Use when a skill, plan, or rule file needs a frozen Starlark governance rule block generated, or an existing frozen block drift-checked against a candidate. Invoke explicitly — not for general rule discussion.
Implement Gale-Shapley stable matching algorithm for two-sided matching problems. Use this skill when the user needs to match candidates to positions, assign students to schools, or solve any two-sided preference matching — even if they say 'optimal job matching', 'stable assignment', or 'candidate-position pairing'.
Fetch a company/product logo from public sources (Clearbit, og:image, favicon) given a brand name or URL, score candidates (wide-aspect + transparent preferred), and archive the best + runner-ups to ~/.lovstudio/logo-collection/<slug>/. Trigger when the user says "find logo", "找 logo", "抓 logo", "收集 logo", "brand asset", "需要 <brand> 的 logo", or wants logos laid out for a website/PPT/poster.
[Hyper] Analyze vague or relayed non-developer stakeholder requests (client, executive, PM, sales/support) by mapping them to codebase impact, presenting interpretation candidates with risks, then implementing only after confirmation. Use for stakeholder-message analysis, not browser QA testing, CI/build failures, or already-clear technical tasks.
Interactively prune stale non-terminal workflows from the pipeline. Use when the user says 'prune workflows', 'clean stale workflows', 'pipeline cleanup', or runs /prune. Runs a dry-run preview, displays candidates with staleness and safeguard skips, prompts the user to proceed/abort/force, then bulk-cancels approved workflows with a workflow.pruned audit event. Safeguards skip workflows with open PRs or recent commits unless force is set.
Investment idea generation — systematically surfaces new investment opportunities by combining quantitative screening (low valuation / high momentum / improving fundamentals), thematic research (sector trends / policy catalysts), and pattern recognition (historical analogues), producing a long/short candidate list. Triggers: "投资想法", "选股灵感", "投资机会", "找股票", "发掘机会", "多头机会", "空头机会", "主题投资", "投資想法", "選股靈感", "投資機會", "找股票", "多頭機會", "空頭機會", "主題投資", "investment ideas", "stock ideas", "investment opportunities", "idea generation", "long ideas", "short ideas", "thematic investing", "stock discovery", "find me stocks", "what should I buy".
Day 2 afternoon move of a Foundation Sprint. Evaluates the candidate approach set through multiple lenses (4 classic plus at least 1 custom) to surface trade-offs, identify consistent winners and contradictions, and produce a top bet plus a backup plan. Use after Approach Options is signed. Lens scoring is a sense-making tool, not mathematical truth; arbitrary precision is a smell.
Execute the /integrate command for LLM agents. Triggers when the user types `/integrate`, `/integrate --product`, or asks to "integrate a Juspay product", "set up payments", "add payment SDK", or any variation of setting up a Juspay product into their app or codebase. This skill drives a fully guided, doc-driven wizard: it reads product summaries locally, probes candidates via MCP, then fetches actual documentation pages and generates complete integration code.
Remediate OS and base-image CVEs in Docker-hosted applications. Use for base image candidate discovery, Docker Scout based comparison, Dockerfile updates, and OS remediation reporting.