「constraint」の検索結果

Cofold protein-ligand, protein-protein, and nucleic-acid complexes with Boltz-2, and predict binding affinity with its trained affinity head. Use this skill to build Boltz input YAML, run structure prediction with MSAs, pocket constraints, templates, and modified residues, screen compound libraries by cofolding, and interpret confidence scores (pLDDT, pTM, ipTM, PDE) and affinity output (binder probability and log10 IC50). Also trigger on Boltz, Boltz-1, Boltz-2, cofolding, boltz predict, affinity_pred_value, affinity_probability_binary, ipTM, or open-weights AlphaFold3 alternatives.

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Use when writing no_std Cortex-M or RISC-V firmware in Rust with cortex-m-rt, probe-rs, defmt, RTIC, or a panic handler. Not for no_std library constraints: use rust-no-std.

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Use when onboarding to a repository, capturing costly conventions, constraints, or rationale, or improving AGENTS.md. Not for remote, credential, publish, deploy, or irreversible changes.

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Audit and migrate specs to the Guarantees + Constraints format. Use when asked to review spec quality, find non-conforming specs, or batch-migrate specs from the old Behaviors/Interfaces format.

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Migrate workloads from Google Cloud Platform to AWS — including AI and agentic workloads regardless of cloud provider. Triggers on: migrate from GCP, GCP to AWS, move off Google Cloud, migrate Terraform to AWS, migrate Cloud SQL to RDS, migrate GKE to EKS, migrate Cloud Run to Fargate, Google Cloud migration, migrate from OpenAI to Bedrock, move off OpenAI, switch from ChatGPT API to AWS, migrate from Gemini to Bedrock, migrate LangChain to Bedrock, migrate LangGraph to AWS, migrate agentic workloads to AWS, move AI workloads to AWS, migrate my AI app to AWS. Runs a 6-phase process: discover GCP resources from Terraform files, app code, or billing exports, clarify migration requirements, design AWS architecture, estimate costs, generate migration artifacts, and collect optional feedback. Clarify must finish before Design, Estimate, or Generate. Includes AI provider migration guidance (for example, OpenAI to Amazon Bedrock) by selecting closest-fit Bedrock model families for required modality, latency/quality targets, context windows, and cost constraints. Model mapping is compatibility-guided, not 1:1 parity; validate prompts, tool-calling behavior, and eval metrics before cutover. Do not use for: Azure or on-premises migrations to AWS, AWS-to-GCP reverse migration, general AWS architecture advice without migration intent, GCP-to-GCP refactoring, or multi-cloud deployments that do not involve migrating off GCP.

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Apply product-grounded visual quality constraints during user-visible UI changes. Use for layout, styling, content hierarchy, theming, responsive behavior, or interaction affordances. Stay inactive for logic-only changes that preserve the rendered interface.

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Use when diagnosing NPU + PyTorch or LLM Serving Host CPU affinity, NUMA locality, cgroup/cpuset constraints, CPU range conflicts, PyTorch/runtime threading, DataLoader, tokenizer, scheduler, vLLM-Ascend, SGLang, TTFT, TPOT, tokens/s, QPS, or multi-rank/multi-worker CPU binding issues.

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Build and verify a vendor-neutral PCB/PCBA manufacturing release from one frozen design revision. Use when generating or auditing Gerber, drill, IPC-2581/ODB++, BOM, CPL/pick-and-place, assembly drawings, constraints, renders, DFM evidence, hashes, or release manifests, and when preventing mixed-revision fabrication or assembly uploads.

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Design, audit, or correct an electronic circuit from a product brief, native schematic, netlist, block diagram, or circuit description. Use for architecture and component-function review, power and logic-domain checks, reset and boot sequencing, bus ownership, ratings, timing, protection, safe states, component suitability, circuit bugs, or layout-facing electrical constraints.

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Audit, finish, or port PCB placement and routing using circuit intent, mechanical constraints, sourcing evidence, native DRC/connectivity, rendered views, and manufacturing feedback. Use before routing, after autorouting, before fabrication release, when adapting a proven board to another connector, enclosure, platform, or regional variant, or when reviewing layers, GND references, power distribution, decoupling, buses, controlled interfaces, RF keepouts, vias, cost-driving features, opens, or DRC findings.

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Operate and review a JLCPCB PCB/PCBA quote, optional physical-stencil request, or order using a frozen Gerber/drill, BOM, CPL, sourcing lock, constraints, and release manifest. Use for browser upload, board or stencil options, cost anomalies, coupons, component matching, substitutions, imported placement calibration, top/bottom preview inspection, cart preparation, or order records without silently accepting placement errors or payment.

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Inventory all founder resources across 8 categories for a one-person company. Use when Codex needs to systematically confirm what resources the founder has — experience, network, skills, relationships, channels, assets, time/money constraints, hard limits — by first doing a broad scan of each category, then drilling into specifics (distribution, usable portions, how to use, cost of use), and producing a confirmed detailed resource inventory written to `opc-doc/`. Does NOT analyze directions, preferences, suitability, or risk tolerance — those belong to downstream skills.

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Flip core assumptions to reveal hidden constraints and alternative approaches - "what if the opposite were true?"

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Generates Claude Code plugin agent .md files: writes YAML frontmatter (name, model, color, tools, hooks, disallowedTools), crafts system prompts, and creates triggering example blocks with context and commentary. Validates agent structure against naming, length, and format constraints. Use when the user asks to create an agent, add an agent, write a subagent, configure agent frontmatter, design agent system prompts, set agent tools or colors, build an autonomous agent, or add agent hooks.

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Create/update .agent/constitution.md. Use when commands/boundaries/constraints must be confirmed before baseline or code changes. Draft v0 from repo evidence, then interview user.

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Pressure-test an assumption, decision, or inherited constraint — Socratic cross-examination that forces you to defend or abandon your position

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Redistricting analysis in R using the redistverse ecosystem. Use whenever the user is working with redist, redistmetrics, ggredist, geomander, adj, alarmdata, PL94171, censable, easycensus, tinytiger, baf, rict, or redistio. Covers the complete pipeline: Census and spatial data loading, adjacency graph construction, SMC/MCMC simulation, constraints (population balance, county splits, VRA compliance), convergence diagnostics, plan metrics (compactness, partisan fairness, splits), visualization, summary tables, and interactive plan drawing. Invoke whenever the user mentions redistricting, gerrymandering, district plans, simulation ensembles, or any redistverse package by name.

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Full-featured Kling 3.0 Omni video generation skill. Covers text-to-video, image-to-video, video editing (base mode), video reference (feature mode), multi-shot generation, and audio-synced video. Includes validated API constraint rules and prompt engineering guide.

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"Apply mechanism design (reverse game theory) to engineer incentive-compatible rules for allocation problems. Use this skill when the user needs to design auctions, voting systems, or matching markets, or when evaluating whether a proposed mechanism satisfies incentive compatibility and individual rationality constraints.".

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"Apply social capital theory (Putnam, Coleman, Bourdieu, Burt) to analyze how network structures and trust generate value or impose constraints. Use this skill when the user needs to evaluate bridging vs bonding capital, identify structural holes or network closure benefits, assess community or organizational trust dynamics, or when they ask 'how does our network create value', 'are we too insular', or 'where are the structural holes we can exploit'.".

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"Apply AI ethics frameworks (fairness, accountability, transparency, privacy) to evaluate AI systems for algorithmic bias, explainability gaps, and value alignment failures. Use this skill when the user needs to audit an AI system for ethical risks, design fairness constraints, assess explainability requirements, or when they ask 'is this AI system fair', 'how do we detect algorithmic bias', 'what are the ethical implications of this AI deployment', or 'how do we make this model explainable to stakeholders'.".

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"Apply the Born Global framework to analyze firms that internationalize rapidly from inception under resource constraints. Use this skill when the user needs to evaluate whether a startup or SME can pursue early internationalization, identify the capabilities enabling born globals, or design a resource-constrained international market entry strategy.".

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"Apply Theory of Constraints (TOC) to identify and manage system bottlenecks. Use this skill when the user needs to find what limits throughput, optimize a constrained process, apply the Five Focusing Steps, or implement Drum-Buffer-Rope scheduling — even if they say 'our output is stuck', 'what's the bottleneck', or 'why can't we produce more'.".

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"Solve vehicle routing problems to optimize delivery routes under capacity and time constraints. Use this skill when the user needs to plan delivery routes, minimize transportation costs, or optimize fleet utilization — even if they say 'delivery route optimization', 'fleet routing', or 'minimize driving distance'.".

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。