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Found 620 Skills
DeFi yield analysis framework — lending rates (AAVE / Compound), liquidity provision (LP) returns, staking yields, yield farming strategies, and risk-adjusted return comparison. Longbridge provides spot crypto prices (`.HAS` suffix) only; DeFi protocol data (APY/TVL) requires DefiLlama/CoinGecko via WebSearch. Triggers: "DeFi收益", "流动性挖矿", "质押收益", "借贷利率", "收益农耕", "LP收益", "AAVE", "Compound", "DeFi协议", "DeFi收益率", "流動性挖礦", "質押收益", "借貸利率", "收益農耕", "DeFi yield", "liquidity mining", "staking yield", "lending rate", "yield farming", "LP returns", "DeFi APY", "TVL", "DeFi protocol", "on-chain yield", "DeFi strategy".
Analyze traces of Claude Code sessions. Use this Skill when users mention session IDs in UUID format (composed of numbers and lowercase letters), time clues such as "just now", "today", "last time", troubleshooting Agent behavior reasons, wanting to view the content of a specific Claude Code session, or analyzing trace content.
Draft CHANGELOG entries from git log via the pm-changelog-curator sub-agent. Dispatches natively on Claude Code with the pm-skills plugin (invokes @agent-pm-changelog-curator); on non-Claude clients (Codex CLI, Cursor, Windsurf, Copilot, Gemini CLI) reads subagents/pm-changelog-curator.md and executes the system prompt inline. Applies CLAUDE.md hygiene rules (no internal-notes references, no em-dashes, no Claude attribution trailers, public paths only). Returns a layered draft (full CHANGELOG draft + Status Summary prose + Status YAML envelope per master plan D26) with hidden justification comments for maintainer audit. Refuses on dirty working tree unless --committed-only is passed.
This skill should be activated when the user requests to "deepen a topic", "analyze a topic", "help me write an outline", "will this topic go viral", "help me diagnose a topic", "is this topic worth pursuing", or "how to improve this topic". Even if the user only shares a topic and asks for opinions, you should proactively initiate the diagnosis process instead of providing a simple response. Driven by the cognitive hijacking theory, it features four modules: Perspective Collision (challenging the topic's premise), Topic Diagnosis (graded using 🛵🚗✈️), Outline Design (emotional peak planning), and Style Validation (alignment with li-writer style). It generates a comprehensive deepening report and saves it as a file. Do NOT trigger this skill for: merely recording topics (use li-recorder), directly writing scripts (use li-writer). Use when the user wants to "develop a topic", "analyze topic potential", "write an outline", "will this topic go viral", or needs full topic diagnosis + outline design. Trigger even if the user just shares a topic and asks for opinions.
Diff a new AI regulation or guidance against your current governance posture — surfaces gaps, priorities, and a remediation plan with owners and deadlines. Use when an AI regulation moves (or you learn about one you missed), or when user says "new reg just dropped", "does [regulation] affect us", "gap analysis for EU AI Act", "compliance check against [AI law or guidance]", or pastes regulatory text.
Builds Moran's I spatial autocorrelation workflows in CARTO. Triggers when the user mentions spatial autocorrelation, Moran's I, spatial dependency, spatial correlation, spatial outliers, HH HL LH LL quadrants, high-high clusters, low-low clusters, spatial weight matrix, "is there clustering", "are values spatially correlated", local indicators of spatial association, LISA, spatial randomness test, or wants to determine whether a variable exhibits spatial clustering, dispersion, or randomness across a gridded dataset. Also relevant when the user needs to classify locations into cluster types (HH, HL, LH, LL) rather than just identifying hotspots and coldspots.
Verify Next.js runtime behavior after editing app code. Use this skill to confirm a change actually works in a running app — not just that it compiles or type-checks. Combines /_next/mcp (Next.js's view) with agent-browser (the browser's view). Requires a running `next dev`.
This skill should be used to search the local Obsidian vault / markdown knowledge base by meaning, not just keywords, using the on-device qmd engine (BM25 + vector + LLM rerank). Trigger when the user asks to "search my vault/notes", "find notes about X", "what do my notes say about Y", "do I have anything on Z", "semantic search my knowledge base", or wants concept/cross-lingual retrieval over markdown. Fully local — nothing leaves the machine.
Code-verification session with the rubber duck — user explains code just written, finds edge cases, fixes planted bugs. Use after implementing a feature, or when they say "duck verify", "재확인해줘". Not for plan review (/duck-plan) or PR review (/duck-review).
A shared, file-based town square where multiple coding agents talk, coordinate, and debate — no server required. Use whenever more than one agent works the same repo (parallel Claude Code or Codex sessions, separate git worktrees, a fleet splitting a task) and they must stay out of each other's way or think together. TRIGGER on phrasings like "coordinate with the other agent/session", "post to / check the agora", "ask the other agents", "leave a message for whoever's working on X", "announce what files you're touching", "is anyone else editing this?", or any time you're about to edit shared code while other agents are live. Also trigger when an agent is stuck and wants a peer's second opinion, or when several agents each drafted a design (an API, a schema, an architecture) and the group needs to compare the proposals and converge on the best one. Works for any agent that can run a Python script, not just Claude Code.
Use when the user wants to store, retrieve, search, or manage files in agent-fs — an agent-first filesystem backed by S3. Triggers on: "save this to agent-fs", "find that file", "store this document", "search agent-fs", "list my files", "show version history", "revert file", "set up agent-fs", "get a signed url", "share this file", "manage members", "invite user", "list members", "remove member", "update role", file persistence for agents, shared agent filesystem, or any mention of the agent-fs CLI. Also use when the user needs to manage drives, manage org/drive members, generate presigned URLs, check recent activity, or use semantic search across stored files. Also use when the user wants to run SQL over stored data files ("query this csv", "sql over my files", "duckdb", "aggregate the parquet file", "query the sqlite db", "join these spreadsheets"). Also use when the user wants to mount or unmount agent-fs as a Linux FUSE filesystem ("mount agent-fs", "fuse mount", "fuse", "remote mount", "sandbox mount", "expose drives as files", "use cat/grep/mv on my agent-fs files", "umount the drive", "mount a remote drive", "mount from sprite", "mount from e2b", "mount from hetzner"). Also use when the user wants to use agent-fs as a just-bash filesystem. Also use when the user wants to set up agent-fs without Docker or S3 ("local filesystem backend", "filesystem storage", "no docker", "onboard --filesystem", "store files on disk"). If the user mentions agent-fs in any context, always consult this skill.
Pentest a web app, API, codebase, repository, URL, domain, or IP with Strix — autonomous AI penetration testing that exploits and proves vulnerabilities (OWASP Top 10 and beyond — injection, XSS, SSRF, auth/access-control flaws, IDOR, business logic) instead of just flagging them. Runs self-hosted with the open-source CLI or via the managed app.strix.ai cloud, and returns validated findings with proof-of-concept exploits (Markdown, JSON, CSV, SARIF). Use when the user asks to pentest, hack, security-scan, security-audit, or find vulnerabilities in an app, API, website, or repo.