1,842 件 ・ 関連度順
概要と使いどころ
Teaches how to reason from a transaction protocol’s rules to a working model. Use when analyzing a concurrency-control paper, spec, or algorithm to identify state, metadata, invariants, operation rules, examples, counterexamples, guarantees, false aborts, unsafe commits, or tradeoffs before inspecting concrete traces.
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。
Comprehensive Content Security Policy audit for MCP Apps in sandboxed iframes. Discovers all network origins, traces them to source, and generates CSP configuration for registerAppResource.
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。
LangSmith tracing and debugging setup for LLM applications. Configure observability, capture traces, and enable debugging for LangChain/LangGraph agents.
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。
Apply when debugging. Trace each symptom to its root cause and fix it there; reproduce first, ask why until you reach it, resist nil-check guards that silence crashes.
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。
Apply when reviewing or shaping code that's hard to trace. Count layers between question and answer, and hidden state in the reader's head; collapse one-caller wrappers and shrink mutable scope.
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。
Fan out N parallel workers, drain them, and return one report. Use for /swarm, 'swarm this', or parallel coverage, races, gauntlets, and exploration.
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。
Deepfake detection and media safety — detect AI-generated audio, images, video, and text, trace synthesis sources, apply watermarks, verify speaker identity, and analyze media intelligence using Resemble AI
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。
WooYun business logic vulnerability methodology — 22,132 real cases across 6 domains (authentication bypass, authorization bypass, payment tampering, information disclosure, logic flaws, misconfiguration) and 33 vulnerability classes. Use for ANY security testing, auditing, or code review of web apps, APIs, or business systems — even without explicit "security" keywords. Triggers: penetration testing, security audit, vulnerability, bug bounty, payment security, IDOR, password reset, weak credentials, unauthorized access, race condition, parameter tampering, code review, 渗透测试, 安全审计, 漏洞挖掘, 支付安全, 越权, 逻辑漏洞, 业务安全, SRC, 代码审计. Also triggers on implicit intent: "test this endpoint", "find bugs", "can I bypass this", "帮我测测这个接口", "这个参数能不能改", "帮我找bug".
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。
Master error handling patterns across languages including exceptions, Result types, error propagation, and graceful degradation to build resilient applications. Use when implementing error handling, designing APIs, or improving application reliability.
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。
Search logs and codebases for error patterns, stack traces, and anomalies. Correlates errors across systems and identifies root causes. Use PROACTIVELY when debugging issues, analyzing logs, or investigating production errors.
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。
You are an error tracking and observability expert specializing in implementing comprehensive error monitoring solutions. Set up error tracking systems, configure alerts, implement structured logging,
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。
You are an error tracking and observability expert specializing in implementing comprehensive error monitoring solutions. Set up error tracking systems, configure alerts, implement structured logging, and ensure teams can quickly identify and resolve production issues.
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。
Master Go concurrency with goroutines, channels, sync primitives, and context. Use when building concurrent Go applications, implementing worker pools, or debugging race conditions.
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。
You are a debugging expert specializing in setting up comprehensive debugging environments, distributed tracing, and diagnostic tools. Configure debugging workflows, implement tracing solutions, and establish troubleshooting practices for development and production environments.
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。
Diagnose Swift Concurrency issues, refactor callback-based code to async/await, and guide Swift 6 migration when working with tasks, actors, @MainActor, Sendable, data races, thread safety, or concurrency-related compiler and linter warnings.
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。
Use when a test fails and you need to diagnose the root cause. Run the test, read errors, trace through generated and source code, fix, and verify.
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。
When a real test is too rare, large, or irreversible, run a controlled counterfactual: isolate one variable, fix conditions, trace the mechanistic chain, and bound what the result implies.
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。
When a change has effects past the immediate fix—incentives, scale, feedback—trace consequence chains with timing and probability before committing.
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。
Build, deploy, evaluate, optimize, fine-tune, and manage Microsoft Foundry agents, models, and resources end to end. USE FOR: foundry, azd ai agent, azd provision/deploy, hosted agent scaffold/develop/run/deploy/troubleshoot, prompt agent create, create agent, update agent, add tool to agent, invoke agent, agent.yaml, agent insights, pull agent insights, evaluate agent, batch eval, continuous eval, continuous monitoring, agent CI/CD, optimize prompt, improve prompt, prompt optimizer, optimize agent instructions, Agent Optimizer scaffold, dataset curation from traces, deploy model, model fine-tuning (SFT/DPO/RFT), Foundry project, RBAC, role assignment, permissions, quota, capacity, region, deployment failure, AI Services, create Foundry resource, knowledge index, customize deployment, onboard, availability, training-data, grader, distillation, large file upload. DO NOT USE FOR: Azure Functions, App Service, general Azure deploy (use azure-deploy), general Azure prep (use azure-prepare).
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。
Performs systematic root cause analysis to identify the true source of bugs, errors, and unexpected behavior through structured investigation phases — not just treating symptoms. Use when a user reports a bug, crash, error, or broken behavior and needs to debug, troubleshoot, or investigate why something is not working; especially for complex or intermittent issues across multiple components. Applies the Five Whys method, hypothesis-driven testing, stack trace analysis, git blame/log evidence gathering, and causal chain documentation to isolate and confirm root causes before applying any fix.
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。
Declarative OpenTelemetry-aligned telemetry vocabulary and instrumentation conventions for traces, metrics, logs, and PII handling
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。
Author and validate durable data and ML feasibility studies using the Feasibility Study Interchange Profile, constrained YAML authority, UUID URN identity, lifecycle lineage, and evidence traceability. Use when assessing whether available data and technical evidence support a proposed outcome.
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。
Build traceable internal-review proposal, RFI, RFP, tender, bid, and questionnaire responses from supplied questions and approved sources. Use to analyze questions, contribute business or product evidence, or draft qualified responses.
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。
Create diverse synthetic test inputs for LLM pipeline evaluation using dimension-based tuple generation. Use when bootstrapping an eval dataset, when real user data is sparse, or when stress-testing specific failure hypotheses. Do NOT use when you already have 100+ representative real traces (use stratified sampling instead), or when the task is collecting production logs.
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。