「contract」の検索結果

Selects, contracts, and manages suppliers and vendors — requirements, evaluation, negotiation support, onboarding, performance management, and exit. Use this to choose a vendor, run a selection process, structure a service agreement's operational terms, manage an underperforming supplier, plan an exit or migration, or assess concentration and continuity risk.

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Covers what the organization owns and what it is only borrowing — trademarks and clearance, copyright and work-for-hire, patents and trade secrets, open-source license obligations and copyleft reach, and IP terms in customer, contractor and AI-tool agreements. Use this to check whether a name is usable, establish that you own work you paid for, decide how to handle a license obligation in a dependency, or respond to an infringement claim.

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Buys well — specifying need, running competitive sourcing, negotiating, and category strategy before a contract exists. Use this to run an RFP or vendor selection, negotiate a purchase, consolidate spend across a category, decide between single and multiple suppliers, or bring uncontrolled spending under management.

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Takes a new customer from signature to working — setting a definition of live that both sides agreed before the contract was signed, planning and staffing the implementation, running data migration and integration realistically, training the people who will actually use it, and handing over to the ongoing relationship. Use this to design an onboarding motion, rescue a stalled implementation, work out why customers who bought never went live, or scope the services a deal actually needs.

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Use when evaluating Mark Minervini-style VCP setups: volatility contraction, tight price action, moving-average alignment, relative strength, breakout trigger, and structural stop placement.

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Use this skill to create fillable Word forms (.docx) with real Content Controls (SDT) + legacy FormField checkboxes + MERGEFIELD mail-merge placeholders + document protection. Trigger on: 'fillable form', 'form fields', 'content controls', 'SDT', 'word form', 'fill in', 'only editable fields', 'protect document', 'onboarding form', 'HR intake', 'survey template', 'contract / SOW template', 'mail-merge template', 'compliance checklist', 'medical intake questionnaire'. Output is a single .docx where specific fields are editable and the rest is locked. This skill is INDEPENDENT, not a scene layer on docx — payload is `<w:sdt>` + `<w:ffData>` + `<w:fldChar>` + `documentProtection`, none of which docx base skill covers. Do NOT trigger for regular reports, letters, memos, academic papers, pitch decks, or any document with no user-fillable fields — route those to officecli-docx or its scene layers.

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Reference for the TRL (Transformer Reinforcement Learning) library codebase. Use proactively before reading or editing any file under `trl/` so you have the intended contracts and invariants in mind, not just what the current code says. Covers trainer hierarchy (SFT, DPO, GRPO, KTO), shared utility functions (selective_log_softmax, decode_and_strip_padding, padding helpers), configuration system, model wrappers, and how data flows through any TRL trainer.

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Drive feature development using Outside-In TDD with Hexagonal Architecture. Design emerges through inline code, in-memory fakes, interface extraction, and deferred I/O. Use when building features, writing tests, or structuring backend services. Triggers on: TDD, outside-in, hexagonal, ports and adapters, emergent design, acceptance test, component test, walking skeleton, in-memory fakes, component, contract test, adapter, fast tests, sub-second feedback. Language-agnostic (Go, Rust, Python, TypeScript, Java, C#).

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Multi-dimensional code assessment across security, quality, performance, and maintainability with confidence-gated reporting (>=80%) and Router Contract generation.

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Translates every clause of a contract from legalese into clear, plain English with flags for deliberately confusing or misleading language

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Clause-by-clause contract risk analysis with severity scoring, financial exposure estimates, and prioritized remediation guidance

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Identifies critical clauses and protections that should be in a contract but are missing, with urgency ratings and ready-to-insert language

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Generate and maintain OpenAPI 3.1 specifications from code, design-first specs, and validation patterns. Use when creating API documentation, generating SDKs, or ensuring API contract compliance.

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Implement NFT standards (ERC-721, ERC-1155) with proper metadata handling, minting strategies, and marketplace integration. Use when creating NFT contracts, building NFT marketplaces, or implementing digital asset systems.

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Implement DeFi protocols with production-ready templates for staking, AMMs, governance, and lending systems. Use when building decentralized finance applications or smart contract protocols.

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Build a dense, data-heavy screen - an analytics console or a trading terminal - with real charts drawn from tokens: candlestick, volume, depth, stacked area, waterfall, scatter, correlation matrix, donut, gauge, sparklines, heatmaps and order books. Use when the request is a dashboard, terminal, monitoring view, data console, or any screen whose job is to show many numbers at once. Covers the layout sequence, the SVG geometry, the accessibility contract per chart type, and the contrast traps that only appear in dark mode.

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From an idea to a sellable series design; series engine / franchise, story pattern, character webs that keep generating conflict, pilot types, and the documents that sell them (剧集引擎/franchise/故事模式/人物网/试播集类型/剧集圣经/跳板/提案). Merged from Rabkin's four-element franchise and story landmines, Landau's tacit contract and pitch recipe, Oberg's series types and bible specs, Douglas's franchise-plus-springboard and bible tiers, Goldberg & Rabkin's 100-episode test, Blum's concept/presentation/bible ladder, Miller's ten-component treatment, Calvisi's Compelling Crisis, Smith's series format, plus engines read off Sopranos, Fleabag and Succession. Use when turning an idea into a series, testing whether a premise has legs, choosing premise vs typical-episode pilot, designing a sustainable character web, writing a logline, pitch document, bible or treatment, picking a series type, adapting IP into a series, or diagnosing a project that feels "more like a movie than a series".

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Before and after changing anything shared — a function's return value, a signature, a schema, a label set, a config default, a constant, a file format — find every consumer and actually run them. Catches the change that looks purely additive but silently breaks a contract in a file you never opened. Use when editing shared code, adding a field/column/return element, renaming, changing units or defaults, or touching a pipeline that produces reported numbers.

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视频脚本洗稿和二创脚本工作流。Use when the user provides an existing transcript, oral draft, viral script, competitor video text, rough topic notes, or wants 洗稿, 二创改写, 爆款视频脚本重写, 逐字稿改成短视频脚本, rewrite with ra-人话, and queue the approved script into 01-内容生产/视频工作台/待制作/ as the handoff contract for video production. If the user provides a video URL or local video file and asks 视频洗稿、视频二创、洗稿并制作视频, use ra-video-wash-pipeline first.

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Use whenever a build emits or repairs .agentlas/routing-card.json — the shared card contract for the single-agent builder, the team builder, and the packager. States what belongs in every field, which fields the hub can actually match on, and which fields silently break matching when a sentence leaks into them.

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Format specifications and data contracts for the security reviewer orchestrator and its subagents.

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Requirements authoring guide for BRD and PRD across Discover, Define, and Govern with canonical templates and handoff contracts

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Create and enrich durable data catalogs using the native DS_CATALOG_V1 Markdown contract, declared entity relationships, privacy citation fields, and stable relationship IDs. Use when inventorying engagement data, recording semantic relationships, or preparing a catalog for ERD rendering.

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Design evaluation datasets and supporting documentation for AI systems and agents, covering the scoping interview, difficulty distribution, dataset contract, sample review, and metric and tooling selection. Use when building or reviewing an evaluation set for a conversational agent, assistant, or retrieval-grounded AI system.

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。