「dynamics」の検索結果

Create comprehensive industry and sector landscape reports covering market dynamics, competitive positioning, key players, and thematic trends. Use for client requests, sector initiations, thematic research pieces, or internal knowledge building. Triggers on "sector overview", "industry report", "market landscape", "sector analysis", "industry deep dive", or "thematic research".

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Framework for building competitive landscape decks — market positioning, competitor deep-dives, comparative analysis, strategic synthesis. Use when the user asks for a competitive landscape, competitor analysis, peer comparison, market positioning assessment, strategic review, or investment memo deck. Also triggers on "who are the competitors to X", "benchmark X against peers", "build a market map", or any request to systematically evaluate competitive dynamics across an industry.

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Extract a sanitized shared team/company brain from a personal brain. Strips internal ratings, compensation, performance assessments, retention and political dynamics from pages, takes, and facts across the full scan scope (people, companies, meetings, dailies, cross-references — not just people/), verifies with grep + retrieval passes, and purges sensitive git history behind the data-loss-gate confirmation card. Also runs as a report-only re-audit on an existing shared brain.

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Perform Porter's Five Forces analysis — competitive rivalry, supplier power, buyer power, threat of substitutes, and threat of new entrants. Use when analyzing industry dynamics, assessing competitive forces, or evaluating market attractiveness.

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Write JavaScript or Python for the n8n Custom Code Tool (@n8n/n8n-nodes-langchain.toolCode) — the AI-agent-callable tool, NOT the workflow Code node. Use when building a Code Tool attached to an AI Agent, writing code that an LLM will invoke, parsing the `query` input, returning a string result, defining an input schema for structured arguments (specifyInputSchema, jsonSchemaExample, DynamicStructuredTool), or troubleshooting errors like "Wrong output type returned", "No execution data available", "The response property should be a string, but it is an object", "Cannot assign to read only property 'name'", or an AI agent that refuses to call the tool. Covers the critical differences between Code node and Code Tool: return format (string vs `[{json:{...}}]`), unavailability of `$fromAI`/`$input`/`$helpers` in the Code Tool sandbox, naming rules for AI invocation, and when to use `toolWorkflow`/HTTP Request Tool 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。

Write JavaScript or Python for the n8n Custom Code Tool (@n8n/n8n-nodes-langchain.toolCode) — the AI-agent-callable tool, NOT the workflow Code node. Use when building a Code Tool attached to an AI Agent, writing code that an LLM will invoke, parsing the `query` input, returning a string result, defining an input schema for structured arguments (specifyInputSchema, jsonSchemaExample, DynamicStructuredTool), or troubleshooting errors like "Wrong output type returned", "No execution data available", "The response property should be a string, but it is an object", "Cannot assign to read only property 'name'", or an AI agent that refuses to call the tool. Covers the critical differences between Code node and Code Tool: return format (string vs `[{json:{...}}]`), unavailability of `$fromAI`/`$input`/`$helpers` in the Code Tool sandbox, naming rules for AI invocation, and when to use `toolWorkflow`/HTTP Request Tool instead.

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Analyzes your campaign history, conversion volume, CPA targets, and auction dynamics, then recommends the right bid strategy for each campaign — manual CPC, target CPA, target ROAS, maximize conversions, or maximize conversion value. Not a blanket recommendation, but campaign-by-campaign based on the data. Platform: Google.

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Visualize, analyze, and render protein and molecular structures using PyMOL. Use when the user wants to create images of protein structures, perform structural alignments or superposition, measure distances or contacts, highlight binding sites or active site residues, color by B-factor/pLDDT, or analyze protein-ligand interactions. Do not use for docking, molecular dynamics, or sequence-only analysis.

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Track bacterial strains using MASH, sourmash, fastANI, and inStrain. Compare genomes, detect contamination, and monitor strain-level variation. Use when needing sub-species resolution for outbreak tracking, transmission analysis, or within-host strain dynamics.

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Tracks ctDNA dynamics over time for treatment response monitoring using serial liquid biopsy samples. Analyzes tumor fraction trends, mutation clearance kinetics, and defines molecular response criteria. Use when monitoring patients during therapy or detecting molecular relapse before clinical progression.

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Assign pathogen lineages and track variants using Nextclade and pangolin for viral surveillance. Monitor variant prevalence and identify emerging variants of concern. Use when classifying viral sequences, tracking lineage dynamics, or monitoring for variants of concern.

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Use when evaluating Bitcoin and crypto cycles through a Willy Woo-style on-chain lens: holder behavior, realized value, supply dynamics, and on-chain demand.

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Use when evaluating stocks through Deng Xiaofeng's cycle-and-industry lens: deep industry research, cycle position awareness, supply-demand dynamics, and buying leaders at cycle bottoms.

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Process meeting recordings and transcripts into decisions, action items, and team dynamics

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Quantum mechanics simulations and analysis using QuTiP (Quantum Toolbox in Python). Use when working with quantum systems including: (1) quantum states (kets, bras, density matrices), (2) quantum operators and gates, (3) time evolution and dynamics (Schrödinger, master equations, Monte Carlo), (4) open quantum systems with dissipation, (5) quantum measurements and entanglement, (6) visualization (Bloch sphere, Wigner functions), (7) steady states and correlation functions, or (8) advanced methods (Floquet theory, HEOM, stochastic solvers). Handles both closed and open quantum systems across various domains including quantum optics, quantum computing, and condensed matter physics.

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Linearizing nonlinear dynamics around operating points for control design.

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Use this skill when simulating vehicle motion, calculating safe following distances, time-to-collision, speed/position updates, or implementing vehicle state machines for cruise control modes.

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Run a family meeting to make a big care decision together. Use when asked help me run a family meeting about care, we need to decide together about mom's care, my siblings and I disagree about our parent, or facilitate a care decision. Produces an agenda and structure for the meeting, how to prepare (facts, options, everyone's input), ground rules to keep old family dynamics from derailing it, how to include the person being cared for, ways to work through disagreement toward a decision, and clear next steps with owners. Not legal, medical, or financial advice.

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Process meeting recordings and notes into structured decisions, action items, and team dynamics with intelligent noise filtering

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Use when targeting Journal of Climate or deciding whether a climate-dynamics or climate-variability manuscript fits this venue. Encodes the journal's fit, the large-scale-climate-science bar, model-evaluation and statistical-rigor expectations, AMS house style, official-submission re-check, and desk-reject heuristics.

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Use when explaining or planning around AISTATS peer review, OpenReview review release, author-reviewer discussion, reviewer volunteer expectations, reviewer confidentiality, decision criteria, meta-review dynamics, the statistician-heavy reviewer pool, and PMLR proceedings outcomes.

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Use when building figures and tables for an Agricultural Systems (AgSy) manuscript so exhibits communicate interactions, dynamics, trade-offs, and model performance clearly. AgSy is a systems journal, so the best exhibits show trade-off frontiers, observed-vs-simulated fit, resource flows, and conceptual system diagrams — not just a bar chart of one treatment. Designs exhibits; it does not run the analysis.

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Use when explaining or planning around ACM CCS peer review, the two-cycle HotCRP workflow, decision categories including minor revision, the rebuttal window, the adversarial reviewer pool, ethics and disclosure scrutiny, meta-review dynamics, and ACM proceedings outcomes.

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Use when drafting an ACL author response inside an ACL Rolling Review cycle on OpenReview, covering the response window before meta-review, reviewer discussion dynamics, score-change strategy, flagging review issues to the area chair, anonymity rules, and deciding between responding now versus revising for a later ARR cycle.

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。