「valuation」の検索結果

Think and work like an expert Biomaterials Scientist. Use when a task calls for Biomaterials Scientist judgment. Reasons from material-biology interfaces, degradation-product toxicity, and mechanical mismatch to host tissue through ISO 10993 biological evaluation plans, ISO 10993-12 extract conditions, GPC/ICP/SEM characterization, and sterilization validation while treating endotoxin contamination, pH shift from acidic degradation, extract-ratio artifacts, and non-final-form test articles as first-class failure modes.

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The Auto 档 scenario — a soft-plan orchestrator for a complete fundamental equity research thesis: understand → financials → valuation → synthesize. The body is a soft plan (stages), not a rigid DAG; correctness is enforced by each referenced skill's own requires: preconditions, never by this plan's rigidity (Q2).

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Financial ratio analysis, profitability ratios ROE ROA ROIC, liquidity ratios current quick cash, leverage ratios debt-to-equity interest coverage, efficiency ratios asset turnover inventory turnover DSO, valuation ratios PE PB EV/EBITDA, cross-company ratio comparison, DuPont analysis

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Med peer benchmarking: select actual biotech/pharma peers via the med universe (drug/indication overlap where possible) and compare med-relevant metrics — pipeline depth, catalyst density, cash position, margins, valuation multiples.

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LBO model, leveraged buyout, private equity acquisition, sources and uses, debt schedule, returns waterfall, sponsor IRR, MOIC calculation, PE exit analysis, LBO valuation

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DCF valuation model, discounted cash flow, intrinsic value, WACC calculation, terminal value, free cash flow projection, equity value per share, DCF sensitivity analysis, unlevered free cash flow, present value calculation, build a DCF

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Patient-flow market sizing for med products — prevalence → diagnosed → interested → affordable → covered → treated → persistent, priced as price × duration per cohort, with capacity constraints, named historical analog anchoring, and always bull/base/bear named-driver grids. Use to size a therapy area or product market before any valuation or share work.

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Quantitative stock screening, forward-looking valuation outlier detection, backward-looking financial statement validation, PEG ratio analysis, earnings growth profile assessment, turnaround vs value trap discrimination, data mining bias prevention

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Comparable company analysis, trading comps, peer multiples, EV/EBITDA comparison, P/E benchmarking, comps table, relative valuation, industry multiples, precedent transactions, trading comparable analysis

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Build, configure, and ship production voice agents on the ElevenLabs Agents platform (branded "ElevenAgents," formerly "Conversational AI"). Use when an agent must design a spoken-conversation system prompt, pick an LLM and TTS voice/model for a real-time voice bot, wire client/server/system tools and knowledge-base RAG, connect a channel (WebRTC/WebSocket SDK, embeddable widget, or telephony via Twilio/SIP), tune turn-taking and latency, set up simulation testing and evaluation, or reason about pricing, concurrency, and the consent/disclosure obligations of a synthetic voice talking to real people. Not for plain non-conversational text-to-speech, dubbing, or music generation.

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Use this skill when an agent needs production image or video understanding with Amazon Rekognition: labels, objects, scenes, OCR, moderation, image properties, Custom Labels or moderation adapters, stored-video analysis, conditional streaming-video workflows for existing eligible accounts, searchable media libraries, confidence evaluation, S3/IAM/event architecture, privacy, biometric consent, cost control, lifecycle management, and QA.

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Use this skill when an agent needs Google Cloud Vision API for still-image understanding: labels, object localization, OCR, document text, SafeSearch, image properties, crop hints, web detection, batch annotation, Cloud Storage based pipelines, confidence evaluation, privacy, quotas, cost, and QA. Do not use it for Gemini multimodal reasoning, video analysis, image generation, custom model training, product catalog search design, or human reference/authenticity review.

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Analyze sentiment in any text — reviews, social posts, feedback, or articles. Returns sentiment polarity (positive, negative, neutral), confidence score, and key phrases driving the sentiment. Useful for brand monitoring, customer feedback analysis, and content evaluation.

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Discover and evaluate KOLs (Key Opinion Leaders) and creators across TikTok, Instagram, YouTube, and Xiaohongshu through SandBase. Use when asked for influencer research, creator outreach lists, KOL evaluation, or partnership prospecting.

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Create, edit, analyze, and verify professional Excel workbooks for general business and operational use. Use when the deliverable is an .xlsx file; use a finance-specific modeling workflow for valuation or regulated financial models.

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End-to-end EHR predictive modeling pipeline with PyHealth, covering dataset loading, task definition, model training, evaluation, calibration, and clinical interpretation.

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Semi-automated fact-checking, source credibility evaluation, misinformation detection, prebunking, and evidence-ledger based claim verification. Use when a user asks to verify a claim, article, social post, screenshot, URL, quote, data point, compare sources, detect manipulation, evaluate source reliability, or generate an HTML fact-check card/share-safe correction. Supports text, URLs, screenshots/images, two-source comparison, and topic-level prebunking in Bulgarian, English, Russian, EU policy, health, science, and geopolitical contexts. Trigger phrases: "is this true?", "is this fake?", "fact check this", "compare these sources", "проверка на факти", "истина ли е", "дезинформация ли е", "сравни тези източници".

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Patterns and techniques for evaluating and improving AI agent outputs. Use this skill when: - Implementing self-critique and reflection loops - Building evaluator-optimizer pipelines for quality-critical generation - Creating test-driven code refinement workflows - Designing rubric-based or LLM-as-judge evaluation systems - Adding iterative improvement to agent outputs (code, reports, analysis) - Measuring and improving agent response quality

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Internal — for Boundless team members only. Query Boundless broker telemetry tables on Redshift for prod/staging operational data. Use when the user asks about broker health, request evaluations, request completions, proving times, skip rates, telemetry data, or wants to run SQL against the telemetry database on live networks. Also covers historical telemetry through 2026-04-24 stored as Parquet archives in S3 (queried via DuckDB). Do NOT use for debugging local code changes, reviewing PRs, or investigating issues in the codebase itself.

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AI SDK for Python (the `ai` package). Use for Python model calls (LLMs, image, video, speech, embedding, transcription, reranking, or evaluation), agents, model interaction tests, tool calling, subagents, approvals, durable execution, telemetry, AI SDK UI backends, and custom providers.

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Use when starting, continuing, updating, exporting, or sharing a running transcript of a MATLAB AI tutoring session, especially when the transcript will be shared with an instructor, attached to a learner session report, or passed to an evaluation workflow for quality review.

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Trim large MetaX model directories for dummy smoke tests or real-checkpoint loading on limited GPUs. Preserve target execution paths while reducing depth; use the real-weight workflow when a loadable checkpoint is requested. Not for accuracy evaluation or model compatibility upgrades.

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60-Second Property Snapshot — quick assessment without subagents for fast property evaluation with signal, key factors, and CTA for full analysis

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Finds and analyzes 5-10 comparable recent sales to estimate fair market value, calculate price adjustments, and score the property's value proposition

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。