「correctness」の検索結果

Official NVIDIA-authored guidance for PhysicsNeMo ShardTensor domain parallelism — integrate domain parallelism into training/inference scripts (new or existing) with DDP or FSDP2, write and register shard patches to enable new layers/ops, and bootstrap multi-GPU correctness tests. Use when working with ShardTensor, scatter_tensor, domain parallelism, sequence/spatial sharding, ring attention, DeviceMesh + DDP/FSDP2 hybrid parallelism, or physicsnemo.domain_parallel. Do NOT use for generic PyTorch DDP/FSDP setup without domain parallelism, picking a PhysicsNeMo model or example (use physicsnemo-discover), or non-distributed training questions.

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Audit openai-go during scheduled or repeated maintainer runs for correctness bugs, security weaknesses, performance problems, rough edges, non-idiomatic Go, test gaps, code organization, and architecture, then report one prioritized recommendation with evidence. Use for recurring proactive repository maintenance and rotating whole-codebase review; do not use for feature work, code changes, autonomous publishing, or pull-request stewardship.

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Exhaustively review committed openai-go pull requests, branches, and commit ranges, or provide best-effort review of uncommitted local changes, for Go correctness, SDK compatibility, generated-code ownership, provider security, and repository-specific gotchas.

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Manually review the implementation diff for the current Comet change. Report correctness, security, and edge-case issues without advancing the workflow.

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Drive a change through a red-green-refactor loop - failing test first, minimal code to pass, then clean up. Use when implementing a feature or fixing a bug where correctness matters and a test can pin the behavior. Says "TDD", "test first", "red green refactor", "write the test first".

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Trigger a pre-merge release readiness review on a GitHub PR, GitLab MR, or local branch. Use when the user wants to analyze code changes for risk, correctness, and potential rollback issues before merging. Trigger words include release readiness, analyze PR, analyze MR, review PR, risk analysis, pre-merge, safe to ship, ready to merge, ready to commit, any risks, before merging, validate changes, release management.

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Audit a target's CORS posture — Access-Control-Allow-Origin handling, reflected-origin bypass, credentials+wildcard mismatch, preflight OPTIONS behavior, Vary header correctness. Use when: a third-party integration is failing CORS preflight and someone proposes "just set Allow-Origin to *" as the fix, OR your bug-bounty inbox has a credential-reuse exploit chain. Threshold: any reflection of arbitrary Origin into Allow-Origin, Allow-Credentials:true with wildcard origin (browser-rejected combo but server config wrong), missing Vary:Origin on per-origin responses, preflight cached over 86400s, OR Allow-Origin trust of attacker- controlled subdomain pattern. Trigger with: "audit cors", "check cors policy", "cors bypass", "preflight check".

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Analyze and improve Attio integration latency and throughput from measured query shape, pagination, concurrency, retry, and cache evidence while preserving correctness. Use when Attio requests are slow or queues are backing up. Trigger with "Attio performance", "speed up Attio sync", or "Attio query tuning".

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Derive a safe Adobe workload envelope from synthetic load, queue/backpressure behavior, current service constraints, spend, and output correctness. Use when the task requires adobe capacity and load envelope. Trigger with "load test Adobe", "scale Firefly jobs", or "Adobe capacity plan".

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Improve Adobe integration latency and throughput from measurements while preserving correctness, policy, and spend boundaries. Use when the task requires adobe measured performance tuning. Trigger with "tune Adobe performance", "reduce Firefly latency", or "optimize PDF jobs".

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Audit a directory of multilingual blog content for completeness, consistency, hreflang correctness, meta-tag parity, and freshness. Builds a translation coverage matrix, flags stale translations, validates hreflang and schema, and emits a prioritized report with runnable fix commands. Use when user says "locale audit", "blog locale-audit", "check translations", "multilingual audit", "translation check", "hreflang check", "Uebersetzungen pruefen".

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Conducts and responds to code review — reviewing a change for correctness, design, and risk, and evaluating review feedback received on your own work. Use this before merging, when asked to review a diff or pull request, when review feedback has arrived and needs acting on, or when feedback seems wrong and needs a reasoned response rather than compliance.

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Review code changes for correctness, security, and maintainability. Supports local git diffs (staged or working tree) and remote Pull Requests (by ID or URL). Use when the user asks to review code, check a PR, audit changes, or wants feedback on code quality before merging.

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Reviews PR(s) using comprehensive review guidelines including security, correctness, clean code, TypeScript, React patterns, i18n/RTL, performance, and accessibility. Use when reviewing pull requests or code changes.

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Comprehensive security and correctness audit of a branch's changes. Use for thermo nuclear, thermonuclear, or deep review requests, or branch/PR diff audits focused on bugs, breaking changes, security issues, devex regressions, and feature-gate leaks.

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Findings-first code review workflow for AI coding agents. Use when the user asks to review uncommitted changes, commits in a date range, or a branch compared to the main branch / PR-style diff. Focuses on bugs, regressions, correctness risks, missing tests, security/data-safety issues, and other behavior-changing defects.

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Automated Planning utilities for loading PDDL domains and problems, generating plans using classical planners, validating plans, and saving plan outputs. Supports standard PDDL parsing, plan synthesis, and correctness verification.

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Compare multiple solutions for correctness and performance

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Identify and verify loop invariants for correctness proofs

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Assist in constructing algorithm correctness proofs

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Generate comprehensive test cases including edge cases, stress tests, and counter-examples for algorithm correctness verification. Supports random generation, constraint-based generation, and brute force oracle comparison.

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Multi-dimensional code review across correctness, security, performance, and maintainability with confidence-gated reporting and remediation loops.

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Use when the user asks to review, verify, or audit a report, manuscript, or analysis in the workspace for traceability — resolving citations, flagging numbers with no source, and checking figures against the code that generated them. Emits a structured review block the app renders as reviewer findings. Verifies traceability, never "correctness".

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You are a configuration management expert specializing in validating, testing, and ensuring the correctness of application configurations. Create comprehensive validation schemas, implement configurat

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。