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Found 1,948 Skills
Retrieve analyst financial estimates including Revenue and EPS projections with low/high ranges and analyst coverage. Use when analyzing forward expectations, consensus estimates, valuation inputs, or comparing projections to historical performance.
Initiating-coverage report framework — five-step workflow to generate an institutional-grade coverage initiation report: ① company overview ② industry positioning ③ financial modelling ④ valuation analysis ⑤ investment conclusion. Covers business description, competitive advantages, financial health, valuation multiples, price target, and risk factors. Triggers: "首次覆盖", "初始覆盖", "覆盖报告", "研报框架", "投资报告", "建立覆盖", "首次評級", "初始覆蓋", "覆蓋報告", "建立覆蓋", "initiate coverage", "coverage initiation", "first coverage", "equity research report", "investment report", "initiating coverage", "research initiation", "NVDA initiate coverage".
Evaluates whether a business idea is technically buildable and financially viable. Covers unit economics (CAC, LTV), revenue modeling, break-even, and go/no-go verdicts. Triggers on: "feasibility assessment", "viability analysis", "unit economics", "build vs buy", "go/no-go decision", "ROI projection".
Interactive config wizard for NeMo Evaluator Launcher (NEL). Use when the user wants to create a new evaluation config from scratch, set up an evaluation from existing configs, or modify a NEL config (deployment, tasks, multi-node, interceptors). ALWAYS triggers on mentions of creating configs, setting up evaluations, configuring models for evaluation, or modifying NEL YAML files. Do NOT use for monitoring, debugging, or analyzing already-running evaluations.
Generate realistic synthetic evaluation datasets by analyzing the user's codebase, prompts, production traces, and reference materials. Interactive, consultant-style — asks clarifying questions, proposes a plan, generates a preview for approval, then delivers a complete dataset uploaded to LangWatch. Use when user asks to generate, create, or build a dataset for evaluation, testing, or benchmarking.
Full brand naming workflow for founders, agencies, and businesses. Use this skill whenever the user says "help me name this brand", "brand naming", "I need a name for", "name ideas for", "what should I call my brand/company/product", "naming a startup", "brand name suggestions", "help with naming", or shares a brand brief and asks for name options. Also triggers when the user shares existing name options and asks for feedback, evaluation, ranking, or scoring of those names. Auto-detects whether to run the full generation workflow or the evaluation workflow based on what the user provides. Always use this skill for any brand or product naming task — even if the user just casually mentions needing a name.
Use when the user wants to evaluate a creator, influencer, or brand audience using public profile signals, TikTok audience demographics, follower/following data, comments, geography, language, and content fit. Helps judge sponsorship and market fit.
Develops resources for FiveM using the QBCore Framework. Covers resource creation, Core Object usage, Player management, Callbacks, Events, Items, Jobs, Gangs, Database (oxmysql), and best practices. Use when the user works with FiveM, QBCore, Lua scripts for QBCore servers, or mentions `QBCore.Functions`, `GetCoreObject`, `CitizenID`, or any system of the QBCore Framework.
Evaluate pricing changes using financial impact analysis - ARPU/ARPA, conversion, churn risk, NRR, and payback. Recommends go/no-go on pricing decisions.
Create a new Harbor task for evaluating agents. Use when the user wants to scaffold, build, or design a new task, benchmark problem, or eval. Guides through instruction writing, environment setup, verifier design (pytest vs Reward Kit vs custom), and solution scripting.
Help a CS or AI PhD student turn a rough research idea into a validated next-step decision using the handbook's FIVE+C framework. Use this skill whenever the user says they have a research idea, wants to know whether an idea is worth pursuing, needs help choosing between project directions, is preparing to pitch an idea to an advisor or senior student, or feels unsure whether a project is too incremental, too ambitious, already solved, hard to evaluate, or missing resources.
AI Agent learning roadmap and curated resources for building production-ready agents with modern patterns like Claude Code, OpenClaw, skills, MCP, and evaluation