自动清洗赛题或爬取的数据(处理缺失/异常/格式),并生成可视化图表。Invoke when 用户需要处理原始数据、清洗数据或生成数据分析图表。
日本語の概要は準備中です。原文の説明を表示しています。
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概要と使いどころ
自动清洗赛题或爬取的数据(处理缺失/异常/格式),并生成可视化图表。Invoke when 用户需要处理原始数据、清洗数据或生成数据分析图表。
日本語の概要は準備中です。原文の説明を表示しています。
自动定位并获取权威公开数据(优先API/官方批量下载),输出可复现抓取与清洗方案。Invoke when用户需要权威数据、官方统计、API下载或数据源爬取。
日本語の概要は準備中です。原文の説明を表示しています。
按常见评分点生成建模论文结构与写作清单,并根据题目类型与数据条件给出模型选择与对照实验路线。Invoke when需要“论文格式/评分对齐/模型选型/路线不确定”。
日本語の概要は準備中です。原文の説明を表示しています。
Manages persistent memory. Invoke to read active context or archive old tasks. Structure: Long-term Principles (Rules) + Short-term Workbench (Tasks).
日本語の概要は準備中です。原文の説明を表示しています。
强制审计论文生成质量,防止模型偷换、逻辑断链、内容空洞。Invoke when 用户提出检查/审计/验收/确保/verify/QA,或合并前需要把关。
日本語の概要は準備中です。原文の説明を表示しています。
解析赛题PDF/Word,抽取任务与数据条件并给出模型选型与验证路线。Invoke when用户提供赛题文档或题目文本,需要确定采用何模型/方法。
日本語の概要は準備中です。原文の説明を表示しています。
Repair a repeatedly failing Standard paper section from repair_queue.json, or generate an explicitly requested legacy/quickstart scaffold. Do not use it as the formal paper writer.
日本語の概要は準備中です。原文の説明を表示しています。
Decision rubric for when an LM agent should write-and-run code (Program-of-Thought / code interpreter) versus reason in natural language: classify each step as deterministic- computable (emit + execute code, feed the result back) vs judgment (stay in prose). Use when designing or debugging an agent step that does arithmetic/parsing/data transforms, when prose reasoning hallucinates a computation (under-coding), or when a sandbox round- trip is wasted on a judgment task (over-coding). Search keywords: code interpreter, agent does math wrong, calculator hallucination, when to run code vs reason, program of thought, PoT, tool vs reasoning.
日本語の概要は準備中です。原文の説明を表示しています。
Builds a founder-led B2B sales motion - ICP and kill criteria, outbound message, first-call and demo plan, pilot and procurement plan, pipeline math, and a readiness check for your first sales hire. Use when you ask about founder-led sales, enterprise sales, cold outreach, ICP, 'why are deals stalling', pilots/POCs, procurement, 'when do I hire a sales rep', or adding sales to a PLG product. Draws on 49 Lenny's Podcast guests incl. Jen Abel, Geoffrey Moore and Pete Kazanjy.
日本語の概要は準備中です。原文の説明を表示しています。
PumpFun bonding curve math, graduation mechanics, instruction parsing, and PumpSwap migration
日本語の概要は準備中です。原文の説明を表示しています。
Search arXiv preprint repository for papers in physics, mathematics, computer science, quantitative biology, and related fields
日本語の概要は準備中です。原文の説明を表示しています。
Provides patterns for testing utility classes, static methods, and helper functions. Validates pure functions, null handling, edge cases, and boundary conditions. Generates AssertJ assertions and @ParameterizedTest for string utils, math utils, validators, and collection helpers. Use when testing utils, test helpers, helper functions, static methods, or verifying utility code correctness.
日本語の概要は準備中です。原文の説明を表示しています。
Builds estimates, quotes, and bids for trades and field-service businesses (HVAC, plumbing, electrical, roofing, landscaping, painting, cleaning, remodeling, general contracting, IT/AV installs). Turns a scope into line items with waste factors, burdened labor, materials, equipment, subs, permits, mobilization, contingency, overhead, profit, and tax, then writes a client-ready xlsx (live formulas) and PDF plus an internal cost sheet, with good/better/best options, add-ons, a payment schedule, exclusions, and assumptions. Use whenever someone asks for a quote, estimate, bid, proposal price, or job price, asks "how much should I charge for this job", wants to check a price or margin on a job, or is confused about markup vs margin. Computes deterministically with a script instead of mental math, because models routinely treat a 30% markup as a 30% margin and drop labor burden, waste, and mobilization.
日本語の概要は準備中です。原文の説明を表示しています。
Answers business questions about the user's own spreadsheet or data export (CSV, TSV, XLSX from a CRM, Shopify, Stripe, QuickBooks, ad platforms, HR or payroll systems) correctly and auditably. Profiles every file first (grain, duplicate keys, embedded Grand Total rows, text-stored numbers, mixed currencies, UTC timestamps, Excel serial dates, hidden rows), states the metric definition used, computes every number in SQL or pandas instead of mental math, checks joins for fan-out, reconciles to a known total, and returns the query, filters, row counts, and rows behind the answer. Use this whenever the user says "analyze this spreadsheet", "how many...", "what's the total in this export", "which customers...", "pivot this", "revenue by month", "top 10", "what's our churn/MRR/AOV", or asks any question about their data, CSV, or Excel file, even a quick one. Also use when they ask to change values in a data file.
日本語の概要は準備中です。原文の説明を表示しています。
Merges, appends, joins, and deduplicates multiple CSV, TSV, and Excel files (including multi-sheet workbooks) with pandas - mapping mismatched column names to one schema, normalizing keys, resolving conflicting values, tracking which file each row came from, and verifying the row math. Use when the user wants to combine spreadsheets or exports, stack monthly files, consolidate contact or lead lists, VLOOKUP-style join two sheets on an ID or email, or dedupe records across sources, even if they only say "put these together" or "clean up these lists into one".
日本語の概要は準備中です。原文の説明を表示しています。
Microsoft 365 / Entra ID attack - tenant discovery, user enumeration via OneDrive differential (2026 verified), AADSTS code reference, Smart Lockout math (hard cap 1-2 attempts/user), ROPC validation, Conditional Access mapping. Wiki-first, FIND schema output.
日本語の概要は準備中です。原文の説明を表示しています。
Create, edit, replicate, import, and export draw.io diagrams with an offline YAML-first workflow: architecture, network topologies, flowcharts, UML/ER, org charts, Mermaid/CSV conversion, existing .drawio bundles, style presets, themes, and non-publication formula diagrams. For publication figures (paper, thesis, IEEE, camera-ready) use drawio-academic-skills instead.
日本語の概要は準備中です。原文の説明を表示しています。
Publication-figure overlay for draw.io. Use instead of drawio whenever the diagram is for a paper, thesis, dissertation, journal, conference, IEEE/ACM submission, manuscript, camera-ready, Word/LaTeX figure, or other publication. Applies venue, figure-type, color, caption/legend, formula, and paper-readability gates for architecture, workflow, roadmap, network-topology, and replicated paper figures.
日本語の概要は準備中です。原文の説明を表示しています。
Create original short videos using the 地下轨迹破土|尺度反转、追逐穿越与空场余波 Creative DNA for MiniMax H3 or Seedance 2.0. Use when the user wants this causal, camera, motion, rhythm, or payoff structure with new subjects and surfaces.
日本語の概要は準備中です。原文の説明を表示しています。
Create original short videos using the 冲击后揭示|从私密困境到城市尺度真因 Creative DNA for MiniMax H3 or Seedance 2.0. Use when the user wants this causal, camera, motion, rhythm, or payoff structure with new subjects and surfaces.
日本語の概要は準備中です。原文の説明を表示しています。
Create original short videos using the 刻意遮断省略|动作升级后以审查卡跳到余波结果 Creative DNA for MiniMax H3 or Seedance 2.0. Use when the user wants this causal, camera, motion, rhythm, or payoff structure with new subjects and surfaces.
日本語の概要は準備中です。原文の説明を表示しています。
Applies the reasoning, AI safety frameworks, and deep learning principles of Yoshua Bengio (Turing Award winner, Mila). Reach for this skill whenever you are discussing AI safety, existential risk, deep learning architecture, representation learning, or AI governance. Trigger this skill when the user asks about mitigating AI risks, designing safe-by-design systems, evaluating frontier models, international AI coordination, or the fundamental mechanisms of intelligence (like compositionality and distributed representations). Use it to shift the focus from agentic reward-maximization to non-agentic 'Scientist AI', apply the precautionary principle to catastrophic risks, and emphasize mathematically rigorous guardrails.
日本語の概要は準備中です。原文の説明を表示しています。
AutoMCM-Pro industrial-grade math modeling agent (Codex CLI binding). Supports AP (AI-led) and Manual (human-spec-led) dual modes with mandatory GitOps checkpoints, forced self-verification of all solver code before LaTeX inclusion, and structured human cross-validation at each pipeline stage. Use for both CUMCM (Chinese) and MCM/ICM (English) competitions.
日本語の概要は準備中です。原文の説明を表示しています。
AutoMCM-Pro industrial-grade math modeling agent (opencode binding). Supports AP (AI-led) and Manual (human-spec-led) dual modes with mandatory GitOps checkpoints, forced self-verification of all solver code before LaTeX inclusion, and structured human cross-validation at each pipeline stage. Use for both CUMCM (Chinese) and MCM/ICM (English) competitions.
日本語の概要は準備中です。原文の説明を表示しています。