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Found 2,206 Skills
Apply principled negotiation using BATNA, ZOPA, and the Harvard method to prepare for and conduct negotiations. Use this skill when the user needs to prepare for a negotiation, evaluate their bargaining position, design win-win solutions, or handle difficult negotiation situations — even if they say 'how do I negotiate this deal', 'what's my leverage', 'they won't budge on price', or 'help me prepare for this meeting'.
Perform break-even analysis to determine the sales volume or revenue needed to cover all costs. Use this skill when the user needs to calculate break-even point, assess margin of safety, evaluate operating leverage, or decide pricing and volume trade-offs — even if they say 'how many units do we need to sell', 'when will we be profitable', or 'what happens if we lower the price'.
Apply DuPont Analysis to decompose Return on Equity (ROE) into profitability, efficiency, and leverage components. Use this skill when the user needs to diagnose why ROE is high or low, compare financial performance drivers across companies, or identify which operational lever to pull — even if they say 'why is our ROE declining' or 'how do we improve returns'.
In-process ClickHouse SQL engine for Python — run ClickHouse SQL queries directly on local files, remote databases, and cloud storage without a server. Use when the user wants to write SQL queries against Parquet/CSV/ JSON files, use ClickHouse table functions (mysql(), s3(), postgresql(), iceberg(), deltaLake() etc.), build stateful analytical pipelines with Session, use parametrized queries, window functions, or other advanced ClickHouse SQL features. Also use when the user explicitly mentions chdb.query(), ClickHouse SQL syntax, or wants cross-source SQL joins. Do NOT use for pandas-style DataFrame operations — use chdb-datastore instead.
Coverage-guided fuzzing workflow for C/C++, Rust, and Go targets. Runs audit-context-building to find suspicious code, writes a targeted harness, builds with sanitizers, runs the fuzzer, and reports crashes.
This skill should be used when a designer is picking up a Task issue to add design coverage. Triggers on phrases like "I want to design task
Workflow Specifications Adapted to Domestic Git Platforms and Team Habits - Full Coverage of Gitee, Coding, Jihu GitLab
Calculate ETF premium or discount relative to Net Asset Value (NAV) using Yahoo Finance data. Use this skill whenever the user asks about an ETF's premium or discount, NAV comparison, whether an ETF is trading above or below its fair value, or wants to compare market price vs NAV. Triggers: "ETF premium", "ETF discount", "NAV premium", "is SPY trading at a premium", "AGG premium to NAV", "market price vs NAV", "ETF mispricing", "BITO premium", "IBIT premium", "bond ETF discount", "trading above/below NAV", "ETF premium screener", "which ETFs have biggest discount", "compare ETF NAV", "ETF arbitrage", or any request involving the gap between an ETF's market price and its underlying value. Also triggers when analyzing leveraged, inverse, international, bond, commodity, or crypto ETFs where premium/discount is a known concern.
Paragraph-level structural blueprint for 10-12 page systems papers targeting OSDI, SOSP, ASPLOS, NSDI, and EuroSys. Provides page allocation, paragraph templates, and writing patterns. Use when user says "写系统论文", "systems paper structure", "OSDI paper", "SOSP paper", or wants fine-grained structural guidance for a systems conference submission.
Ultra-lightweight channel for refactor processes - used when changes are clearly too small to go through the full scan → design → apply three-stage workflow. AI directly identifies 1-3 low-risk optimization points, confirms with the user once, modifies in-place using classic methods, and validates itself by running tests. No scan checklist, no design documentation, no multi-step human verification required. Trigger scenarios: User says "quick refactor", "small refactor", "simply optimize XX function", "modify directly", "skip the extra steps", and the scope of changes is clearly localized to a single function / single component with test coverage for self-validation.
Applies Geoffrey Moore's chasm-crossing strategy for B2B tech products moving from visionary early adopters to pragmatist mainstream. Use when a product has early traction but stalls before mainstream adoption, when planning a beachhead/niche strategy, when designing whole-product offerings, when positioning against established competitors, or when scaling from innovator usage to industry standard. Triggers include 'stuck between early adopters and mainstream', 'we need a beachhead', 'pragmatist customers won't buy', 'how do we go from 10 to 1000 customers'. NOT for PLG/freemium SaaS (Slack, Notion, Cursor), pure consumer apps, two-sided marketplaces, or AI-native products with bottoms-up viral adoption - their dynamics break the visionary-to-pragmatist sequence.
Adapt an ML paper's writing, structure, positioning, and paragraph-level narrative to a target conference such as NeurIPS, ICML, ICLR, CVPR, ACL, EMNLP, or similar venues. Use this skill whenever the user wants to submit, rewrite, polish, restructure, or tailor a paper for a specific conference; asks what good accepted/oral papers at a venue look like; wants reviewer-friendly writing; or wants section-by-section or paragraph-by-paragraph paper guidance. This is a writing and presentation skill, not an experiment-design skill.