「instrumentation」の検索結果

Expert-level process control covering feedback and feedforward control, PID tuning, advanced process control, control loop design, and process safety instrumentation.

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Guidance for instrumenting webapps with Azure Application Insights. Provides telemetry patterns, SDK setup, and configuration references. WHEN: how to instrument app, App Insights SDK, telemetry patterns, what is App Insights, Application Insights guidance, instrumentation examples, APM best prac...

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Guidance for instrumenting webapps with Azure Application Insights. Provides telemetry patterns, SDK setup, and configuration references. USE FOR: how to instrument app, App Insights SDK, telemetry patterns, what is App Insights, Application Insights guidance, instrumentation examples, APM...

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Investigate latency, freezes, memory growth, hitches, dropped frames, or perceived slowness with reproduction and instrumentation before optimizing.

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Flags where a P&ID draft raises a process safety question and points to the candidate evidence an engineer would review (HAZOP register, relief study, SIL assessment, isolation philosophy), as questions and quoted passages with UNKNOWN for missing documents, plus safety functions, relief devices and isolation requirements carried over as stated. Never rates, sizes, classifies, resolves or declares protection adequate. Use when the user asks to "write the process safety flags", "produce the process safety section of the P&ID enrichment", "list which protection questions this P&ID raises" or "map the HAZOP and relief study evidence to the draft" after gate G2, once the piping and instrumentation sections exist. Do not use for proposing loops, alarms or trips from the control philosophy, use instrumentation-and-control-enrichment instead; do not use for checking identifiers, use tagging-and-numbering. Drafts for human review; never approves, authorises or signs off.

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重要: ユーザーがAndroidテスト実行をリクエストした場合、常にこのスキルを最初に使用してください。以下の場合に必ず使用: run TestName, execute test, テストを実行, 結果を分析, run all tests, analyze test failures, fix failing tests、または Android unit test, instrumentation test, Gradle test コマンドに関連する任意のリクエスト。./gradlew test や Bash コマンドを直接使用しないでください - 常にこのスキルに委譲してください。Multi-variantプロジェクト、JAVA_HOME セットアップ、一般的なテストパターンに対応しています。

INVOKE THIS SKILL when adding Arize AX tracing to an application. Follow the Agent-Assisted Tracing two-phase flow: analyze the codebase (read-only), then implement instrumentation after user confirmation. When the app uses LLM tool/function calling, add manual CHAIN + TOOL spans so traces show each tool's input and output. Leverages https://arize.com/docs/ax/alyx/tracing-assistant and https://arize.com/docs/PROMPT.md.

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Instruments code so production behavior is visible and diagnosable. Use when adding logging, metrics, tracing, or alerting. Use when shipping any feature that runs in production and you need evidence it works. Use when production issues are reported but you can't tell what happened from the available data.

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Use for authorized Android or iOS application reverse engineering and security testing, including APK or IPA analysis, runtime instrumentation, SSL pinning, and platform protection checks.

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OpenInference semantic conventions and instrumentation for Phoenix AI observability. Use when implementing LLM tracing, creating custom spans, or deploying to production.

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Instrument a webapp to send useful telemetry data to Azure App Insights

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Cross-session environment retrospective driven by OMC's own instrumentation — trace timelines, friction reports, logs, and plan notepads. Every finding lands on the surface that owns the fix (deterministic check, steering volume, tooling, or information access); nothing is written without user approval.

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Detects and analyzes malicious behavior in mobile applications through behavioral analysis, permission abuse detection, network traffic monitoring, and dynamic instrumentation. Use when analyzing suspicious mobile applications for data exfiltration, command-and-control communication, credential stealing, SMS interception, or other malware indicators. Activates for requests involving mobile malware analysis, app behavior monitoring, trojan detection, or suspicious app investigation.

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Reproduce and measure a Mastra Code runtime bug against a real model by driving the built TUI headlessly in tmux while every layer (network, provider stream, run engine, TUI) appends timestamped JSONL. Use when a bug depends on real provider timing, streaming order, or event flow that mocked tests and fixtures may not reproduce — e.g. wrong token rates, flicker, stuck status, ordering races, or "only happens sometimes with a real model".

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Sets up and runs AFL++ for multi-core fuzzing of C/C++ projects built with afl-clang-fast or afl-gcc-fast. Covers instrumentation modes, parallel main and secondary campaigns, persistent mode, corpus minimization, and crash triage. Use when scaling fuzzing across cores, fuzzing a mature C/C++ codebase, reading the afl-fuzz status screen, or moving on after libFuzzer has plateaued.

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Mobile (Android + iOS) application penetration testing methodology. Covers static analysis (apktool/jadx for Android, class-dump/Hopper/IDA for iOS), dynamic instrumentation with Frida and Objection, SSL pinning bypass strategies, root/jailbreak detection bypass, deep-link / URL-scheme abuse, exported component attacks (Android activities, services, providers, receivers; iOS XPC, URL schemes, universal links), insecure data storage (SharedPrefs, KeyStore misuse, NSUserDefaults, Keychain ACL bypass), IPC / Intent redirection, WebView vulnerabilities (JavaScriptInterface, file:// access), Firebase/AWS/Azure misconfiguration leakage, mobile API testing, biometric/Face ID/Touch ID bypass, app-cloning and runtime patching, and mobile malware/RAT analysis primitives. Use for mobile pentest, bug bounty mobile triage, or app-store reconnaissance.

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The way to answer "how are my production AI agents doing?" and to run the team's agent-observability deployment — reach for it even on casual phrasing that names no tool. Trigger when the user wants to: • inspect agent telemetry — did agents error/fail/go flaky; sessions, events, latency, token usage, slowest models; eval/quality scores and whether quality dropped; • operate the deployment — ack/assign/resolve/mute/dismiss issues (alerts, reports, and audit findings) with notes; run and triage audits; see who has access and change roles (e.g. read-only); create or scope API keys (e.g. a push-only CI key); change settings; run saved or ad-hoc ClickHouse queries. Served by the `fp` CLI against FailproofAI Cloud. NOT for writing or designing an evaluator service / scoring logic (that's `agenteye-evaluator`), adding SDK/instrumentation to your app (that's `failproofai-sdk`, imported as `failproofai_sdk`), debugging the collector/daemon, or unrelated dev work (why a build/CI run failed, rotating non-FailproofAI Cloud secrets).

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End-to-end iOS red-team pipeline — IPA acquisition (App Store extraction, TestFlight, enterprise/ad-hoc sideload), class-dump/Hopper/Ghidra static analysis, Info.plist + entitlements + Keychain secret extraction, App Transport Security (ATS) misconfig + certificate-pinning bypass (frida-ios-dump, objection, SSL Kill Switch 2), URL-scheme / Universal Link hijack, exported-service enumeration, Frida runtime instrumentation. Companion to apk-redteam-pipeline for the iOS side of a mobile app catalogue. Use when target has an iOS app (App Store listing, TestFlight link, enterprise MDM distribution), when an IPA URL is found hosted on a web server, or when post-recon mentions "iOS app" / "mobile app" in scope alongside an Apple developer account.

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End-to-end Android APK red-team pipeline — automated APK acquisition (Play Store + apkpure + apkmirror fallback), jadx decompilation, secret/URL/JWT/Firebase grep, pinned-cert extraction, exported-component enumeration, Frida runtime instrumentation templates, intent-injection probes. Built from an authorized external red-team engagement where 7 APKs were pulled manually, 4 download attempts truncated, and a hardcoded JWT + 30 internal API endpoints were recovered from one of the apps. Use when target has a mobile app catalogue (Play Store developer page), when you find an APK URL hosted on a web server, or when post-recon mentions "mobile app" in scope.

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Debug the running local stack with traces, logs, and a shared headless browser. Use when investigating a bug in a running service, tracing a request across services, reading service logs, reproducing a frontend issue, or writing/reviewing tracing instrumentation.

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Add gcov code coverage instrumentation to C/C++ projects

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Instrument C/C++ with -finstrument-functions for execution tracing and Perfetto visualisation

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Dynamic instrumentation via Frida - attach to or spawn a process, load a JS hook script, capture send() events into a lifecycle-managed run directory. Supports local, USB-attached, and remote frida-server targets.

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Use this skill when first-time NeMo Relay users want to try Relay, choose the least-complex supported quick start, or verify initial value through the CLI, a maintained integration, or direct Python, Node.js, or Rust instrumentation before production setup.

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