「structure」の検索結果

Structured planning mode for AI agents working on coding and development tasks. Produces a comprehensive plan BEFORE any code is written or changed, including task decomposition, architecture decisions, risk assessment, and approval gates. Use this skill whenever the user says "/plan", "plan mode", "plan first", "think before coding", "make a plan", or asks the agent to plan before executing. Also trigger when the user describes a complex multi-step development task and would clearly benefit from structured planning before implementation — especially for tasks involving new features, refactors, migrations, infrastructure changes, or multi-file edits. When in doubt, plan. A few minutes of planning prevents hours of rework.

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Generate comprehensive status reports for git repositories. Analyzes commits, codebase structure, type errors, branch health, dependency status, GitHub PRs/issues/CI, working tree changes, and optionally integrates with `td` (task management CLI) if a `.todos` folder is present. **TRIGGERS - Use this skill when:** - User asks for the status of a git project or repo - User asks "what's going on in [project]" or "give me an overview of [repo]" - User wants a project summary, progress report, or codebase overview - User asks about recent commits, code structure, or project health - User says "check my project" or "project status" **Output:** A rich, structured text report covering overview, branches, commit history, codebase breakdown, GitHub activity, dependency health, issues/errors, working tree changes, task management, and summary.

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Use Neo4j GenAI Plugin ai.text.* functions and procedures for in-Cypher embedding generation, text completion, structured output, chat, tokenization, and batch ingestion. Covers ai.text.embed(), ai.text.embedBatch(), ai.text.completion(), ai.text.structuredCompletion(), ai.text.aggregateCompletion(), ai.text.chat(), ai.text.tokenCount(), ai.text.chunkByTokenLimit(), and provider configuration for OpenAI, Azure OpenAI, VertexAI, and Amazon Bedrock. Requires CYPHER 25. Replaces deprecated genai.vector.encode(). Use when writing pure-Cypher GraphRAG, embedding nodes in-graph, generating structured maps from prompts, or calling LLMs inside Cypher queries. Does NOT handle neo4j-graphrag Python library pipelines — use neo4j-graphrag-skill. Does NOT handle vector index creation/search — use neo4j-vector-index-skill.

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Designing LLM-optimized folder structures: audits and restructures directories for context efficiency, progressive disclosure, and prompt cache performance. Not for general repo structure (Grove).

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When the user wants to add, fix, or optimize schema markup and structured data on their site. Also use when the user mentions "schema markup," "structured data," "JSON-LD," "rich snippets," "schema.org," "FAQ schema," "product schema," "review schema," "breadcrumb schema," "Google rich results," "knowledge panel," "star ratings in search," or "add structured data." Use this whenever someone wants their pages to show enhanced results in Google. For broader SEO issues, see seo-audit. For AI search optimization, see ai-seo.

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Use the corp-finance-mcp server tools for specialty finance, regulatory, and compliance calculations. Invoke when performing private credit (unitranche, direct lending, syndication), insurance (loss reserving, premium pricing, Solvency II SCR), FP&A (variance analysis, break-even, working capital, rolling forecast), wealth management (retirement planning, tax-loss harvesting, estate planning), restructuring (recovery analysis, distressed debt), real assets (property valuation, project finance), venture capital (dilution, convertible instruments, fund returns), ESG (scoring, climate/carbon, green bonds, SLL), regulatory capital (Basel III, LCR/NSFR, ALM), compliance (MiFID II best execution, GIPS reporting), credit derivatives (CDS pricing, CVA/DVA), convertible bonds (binomial tree pricing, scenario analysis), lease accounting (ASC 842/IFRS 16, sale-leaseback), pension & LDI (funding analysis, liability-driven investing), sovereign risk (bond analysis, country risk), real options (binomial valuation, decision trees), equity research (SOTP, target price), commodity trading (spread analysis, storage economics), treasury management (cash management, hedge effectiveness), infrastructure finance (PPP models, concession valuation), crypto (token valuation, DeFi analysis), municipal bonds (pricing, credit analysis), structured products (notes, exotic), trade finance (LC, supply chain), fund structuring (US onshore, UK/EU, Cayman/BVI offshore, Luxembourg/Ireland), transfer pricing (BEPS/Pillar Two, intercompany pricing), tax treaty (treaty network optimization, holding structures), FATCA/CRS (reporting, entity classification), economic substance (multi-jurisdiction testing), regulatory reporting (AIFMD Annex IV, SEC Form PF, CFTC CPO-PQR), AML compliance (KYC risk scoring, sanctions screening), fund of funds (J-curve, commitment pacing, manager selection, secondaries pricing), bank analytics (NIM analysis, CAMELS rating, CECL provisioning, deposit beta, loan book), carbon markets (credit pricing, ETS compliance, CBAM, offset valuation, shadow carbon price), private wealth (concentrated stock, philanthropic vehicles, wealth transfer, direct indexing, family governance). All computation uses 128-bit decimal precision.

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Build production-grade infrastructure as code for a service or project. Use when asked to "set up infra", "provision infrastructure", "create cloud resources", "IaC for this project", "terraform for this", or "deploy this service".

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Design or review org structure - spans of control, reporting lines, role clarity, headcount plan, and team topology. Use when asked to "design our org", "should we restructure", "what is the right team structure", or "plan headcount for next year".

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Infrastructure reconnaissance — inventory all cloud resources, map connections, flag risks. Use when asked to "inventory our infra", "what infrastructure do we have", "map our cloud resources", "infra discovery", or "what's running in our cloud".

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Symbolic manipulation, equation solving, and algebraic structures for mathematical reasoning. Covers distributive law, factoring, completing the square, linear through polynomial equation solving, systems of equations (substitution, elimination, Gaussian elimination, matrix methods), algebraic structures (groups, rings, fields), modular arithmetic, polynomial theory, and inequalities. Use when solving equations, simplifying expressions, working with algebraic structures, or performing symbolic manipulation.

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Grammar and syntactic structures across human languages -- word order typology (SVO, SOV, VSO, VOS, OVS, OSV), morphological systems (isolating, agglutinative, fusional, polysynthetic), agreement patterns (gender, number, case, person), phrase structure, clause embedding, and cross-linguistic universals. Covers constituent analysis, dependency vs. constituency grammars, grammatical relations (subject, object, oblique), ergativity vs. accusativity, tense-aspect-mood systems, and how grammar encodes meaning differently across language families. Use when analyzing sentence structure, comparing grammar systems, teaching grammatical concepts, or understanding why a learner makes transfer errors from their L1.

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Design, create, inspect, update, attach, detach, preview, execute, and verify reusable Vapi Structured Outputs through public API or Server SDK workflows. Use for post-call extraction, typed call artifacts, AI-versus-regex extraction, JSON Schema design, backfilling existing calls, or retrieving structured results programmatically.

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Use this skill when architecting new Claude Code agents following Anthropic best practices. Guides through YAML frontmatter creation, agent structure definition, role boundaries, and validation. Critical for creating minimal agent files (~150 lines) with proper skill invocations. Examples: <example>Context: User wants to create a new agent for security auditing user: "Create a security-auditor agent" assistant: "I'll use the agent-creator skill to build this agent following Anthropic best practices" <commentary>New agent creation requires the agent-creator skill to ensure proper structure and YAML frontmatter.</commentary></example> <example>Context: Existing agent file is too verbose and needs refactoring user: "The architect agent is 2000 lines, refactor it to minimal structure" assistant: "I'll use the agent-creator skill to refactor this into a minimal ~150 line agent with a separate skill file" <commentary>Agent refactoring requires the agent-creator skill to separate identity from technical procedures.</commentary></example>

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Generates Remotion composition structure focusing ONLY on Sequence ordering, scene transitions, and duration mapping. Input is scene list with durations. Output is COMPOSITION_STRUCTURE.md with Sequence layout and timing calculations. Use when organizing scenes or when asked to "structure composition", "layout scenes", "calculate timing".

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Analyzes inflation protection mechanisms in infrastructure with CPI-linked revenues, index-based contracts, and real return modeling. Use when modeling inflation linkage, analyzing CPI adjustment, or evaluating real return profiles.

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Builds revolving securitization models with replenishment criteria, early amortization triggers, and portfolio composition limits. Use when modeling revolving structures, analyzing credit card ABS, or evaluating asset purchase criteria.

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Assesses infrastructure fund secondaries with asset-level cash flow analysis, concession period evaluation, and regulatory risk assessment. Use when analyzing infra secondaries, evaluating infrastructure assets, or pricing infra fund interests.

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Evaluates rating agency methodology application with loss model inputs, correlation assumptions, and tranche-level credit assessment. Use when analyzing structured product ratings, comparing agency methodologies, or assessing rating sensitivity.

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Evaluates water treatment, waste management, and environmental services assets with regulatory compliance and growth drivers. Use when analyzing water infrastructure, evaluating waste assets, or assessing utility investments.

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Evaluates transportation assets with ridership analysis, fare structure assessment, and operating efficiency benchmarking. Use when analyzing transportation projects, evaluating mass transit, or assessing toll road economics.

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Evaluates market structure dynamics with order book analysis, spread decomposition, and information asymmetry assessment. Use when analyzing market structure, evaluating trading venues, or assessing execution quality.

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Evaluates data centers, fiber networks, and tower assets with capacity analysis, tenant credit, and technology obsolescence risk. Use when analyzing digital infrastructure, evaluating tower portfolios, or assessing data center investments.

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Evaluates CDS, CDX, and bespoke credit derivative structures with spread analysis and credit event mechanics. Use when analyzing credit derivatives, pricing CDS, or evaluating index tranche products.

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Applies best practices for logging (zerolog/zap), project structure (cmd/internal/pkg), middleware registration order, and environment configuration in Go Fiber v2/v3 applications.

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。