Query token security audit to detect scams, honeypots, and malicious contracts before trading. Returns comprehensive security analysis including contract risks, trading risks, and scam detection. Use when users ask "is this token safe?", "check token security", "audit token", or before any swap.
Per-token details for a specific token identified by keyword, symbol, or contract address: (1) search — find tokens by keyword/symbol/contract; (2) meta — static info: name, symbol, logo, social links, creator, official website; (3) dynamic — real-time market data: price, 24h change, volume, holder count, liquidity; (4) kline — OHLCV candlestick data for technical analysis. Use for: "price of $X", "search for token Y", "kline chart for $Z", "who created $W", "social links for $V", "holder count of $U", "candlestick data", "find the contract address of <token>".
Use when the user wants to publish new content to Binance Square — short text, multi-image posts (up to 4), long-form articles with an optional cover, or videos with an auto-generated cover frame. Trigger on direct phrasings like "post to Square", "publish to Binance Square", "发广场", "发布到广场", and on near-miss intents where the user clearly wants to share or publish content on Square even without naming the skill: "share this analysis on Square", "把这篇文章发出去", "发个动态", "把这个视频上传到广场", "publish my chart to Square as an article". Also use when the user provides media (images, video) plus a caption and asks to push it to Square, or asks to turn a draft into a Square article. Do not use for reading, searching, commenting, liking, editing, deleting, scheduling, or managing existing Square posts — this skill only creates new posts.
Competitor research and intelligence skill. Takes a user's company (with optional seed competitor URLs), auto-discovers additional competitors via Browserbase Search API, deeply researches each using a 4-lane pattern (marketing surface, external signal, public benchmarks, strategic diff vs the user's company), and compiles the results into an HTML report with four views: overview, per-competitor deep dive, side-by-side feature/pricing matrix, and a chronological mentions feed (news, reviews, social, comparison pages, and public benchmarks). Use when the user wants to: (1) analyze competitors, (2) build a competitive matrix, (3) extract competitor pricing / features, (4) find comparison pages and online mentions of competitors, (5) surface public benchmarks. Triggers: "competitor analysis", "analyze competitors", "competitive intel", "competitor research", "competitor pricing", "feature comparison", "price comparison", "find comparisons", "who's comparing us", "competitor mentions", "competitor benchmarks".
APM - install, onboard, instrument, enable, set up, configure, traces, services, dependencies, performance analysis. Use for any request involving Datadog APM setup, instrumentation (SSI, ddtrace, agent install), or analysis.
Analyze LLM experiment results. Handles single or comparative experiments, exploratory or Q&A modes. Use when user says "analyze experiment", "compare experiments", "analyze against baseline", or provides one or two experiment IDs for analysis.
Root cause analysis on production LLM traces. Diagnoses why an LLM application is failing — works from eval judge verdicts, runtime errors, or structural anomalies depending on what signals are present. Walks the span tree from symptom to root cause. Use when user says "what's wrong with my app", "why is my eval failing", "analyze errors", "root cause analysis", "diagnose failures", or wants to understand production failure patterns.
Create a company research brief with executive quotes, product strategy, and org context. Use when preparing for interviews, competitive analysis, partnerships, or market-entry work.
Look up SaaS finance metrics, formulas, and benchmarks fast. Use when you need a quick metric definition, formula, or benchmark during analysis.
Analyze political, economic, social, technological, environmental, and legal forces. Use when external market shifts could materially affect a product, roadmap, or strategy.
Analyze A/B test results with statistical significance, sample size validation, confidence intervals, and ship/extend/stop recommendations. Use when evaluating experiment results, checking if a test reached significance, interpreting split test data, or deciding whether to ship a variant.
Perform cohort analysis on user engagement data — retention curves, feature adoption trends, and segment-level insights. Use when analyzing user retention by cohort, studying feature adoption over time, investigating churn patterns, or identifying engagement trends.