「canary」の検索結果

Test AI/LLM features that ship in your product. Covers prompt regression testing, response quality evaluation, tool-call validation, hallucination and RAG grounding checks, nondeterministic-output strategies, red-team/safety scans, eval frameworks, and agent-as-target injection (indirect injection via tool output / RAG / scan reports, self-propagating payloads, data exfiltration via an agent) plus a bundled detector for untrusted content. Use when: "test our LLM feature," "prompt regression test," "eval framework," "hallucination test," "RAG grounding," "nondeterministic output," "AI feature testing," "red-team our chatbot," "indirect prompt injection," "agent reading untrusted tool output," "production AI quality." Not for: using AI to generate your own test code — use ai-test-generation. Not for: classifying CI failures with AI — use ai-bug-triage. Not for: EU AI Act / GDPR conformity of an AI feature — use compliance-testing. Not for: canary/flag rollout of an AI feature — use testing-in-production. Related: ai-test-generation, ai-qa-review, api-testing, compliance-testing, security-testing, risk-based-testing, test-data-management.

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Miro presents itself as the AI-powered visual workspace through a confident, almost playful brand voice — anchored by its signature canary yellow ({colors.brand-yellow}) wordmark over white canvas, broken open by colorful pastel feature tints (rose, teal, coral, orange, mint) that echo the actual sticky-note color palette used on the live whiteboard. Black-pill primary buttons dominate marketing, real Miro-board mockups serve as feature illustrations, and a 4-tier pricing grid leads into a dense comparison table. Roobert PRO carries display headlines; the system supports homepage, pricing, AI Workflows product page, agile vertical, and customer stories surfaces.

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World-class continuous integration and deployment - GitHub Actions, GitLab CI, deployment strategies, and the battle scars from pipelines that broke productionUse when "ci/cd, cicd, pipeline, github actions, gitlab ci, circleci, jenkins, workflow, deployment, deploy, release, blue green, canary, rollback, build, test automation, continuous integration, continuous deployment, cicd, github-actions, gitlab-ci, deployment, automation, devops, pipelines, continuous-integration, continuous-deployment" mentioned.

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Configures Envoy, the high-performance C++ edge and service proxy, as an API gateway, load balancer or service mesh sidecar with L4/L7 routing, retries, circuit breaking, rate limiting, TLS and observability. Use when a user asks to set up Envoy, write an envoy.yaml, route traffic to backends, add health checks or rate limits, do a canary split, read Envoy admin stats, or understand the proxy behind Istio and Envoy Gateway.

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Audit whether a paper's EVALUATION DESIGN actually measures what it claims and whether its reporting is complete — the validity layer family D (experiment-forensics) cannot reach. Three patterns: train/test leakage means the reported score may not measure generalization (HP-EVAL-LEAKAGE — adopts the Kapoor & Narayanan 8-type / 3-category leakage taxonomy; the illegitimate-proxy / sampling-bias / pretraining-contamination subtypes hand off as needs_external_check, naming but NEVER running Oren-2023 exchangeability / Shi-2023 Min-K% / Golchin-2023 Time-Travel / BIG-bench canary); a load-bearing LLM judge is conflicted (same model/family as a compared system) or unvalidated (no human-agreement, no bias control) (HP-JUDGE-VALIDITY); a declared condition/metric is dropped or switched to favor the method, or 'best' is chosen with no held-out set (HP-SELECTIVE-REPORTING). Verdict-bearing at L0/L1 from the DESCRIBED protocol — NOT repo-gated like experiment-forensics; L2 only CONFIRMS against split/preprocessing/result files. A fresh cross-model reviewer (gpt-5.6-sol xhigh, read-only, fresh thread per pass) PROPOSES findings, each span-anchored to a ledger claim_id; tools/adjudicate_findings.py DECIDES the verdict. Leakage and under-reporting are usually HONEST methodological errors — every finding describes a discrepancy to CHECK, never an accusation. An LLM generating GROUND-TRUTH labels is HP-FAKE-GT (experiment-forensics) — routed there, not here. Emits eval-design-forensics.findings.json; computes NO verdict. Detect-only. Triggers: "eval design audit", "evaluation validity", "train/test leakage", "data leakage", "is the score measuring generalization", "LLM judge bias", "is the judge validated", "selective reporting", "cherry-picked results", "评估设计审计", "评测有效性", "数据泄漏", "训练测试集泄漏", "裁判模型有没有验证", "选择性报告".

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Design CI/CD pipelines for GitHub Actions, GitLab CI, and CircleCI with matrix builds, test sharding, caching, Docker layer caching, OIDC auth, deployment strategies (rolling, blue-green, canary), auto-rollback, self-hosted runners, and environment protection with manual approvals. Use when user asks to set up CI/CD, write a pipeline, configure GitHub Actions/GitLab CI/CircleCI, automate deployments, or set up build/test/deploy workflows. Do NOT use for Dockerfile authoring (use docker), K8s manifests (use kubernetes), or Terraform config (use terraform).

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Runs production ML and LLM systems. Use when deploying, canarying, rolling back, monitoring drift or feature skew, promoting champions, migrating providers, or handling incidents.

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Expert guide for Feature Flags & Progressive Rollout (PostHog, LaunchDarkly, GrowthBook), A/B testing orchestration, and canary releases / Panduan ahli Feature Flags, A/B testing, dan rilis bertahap.

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Provides release management strategies including deployment patterns, version control, and rollback procedures. Use when planning releases, managing deployments, or when user mentions 'release', 'canary', 'blue-green', 'rollback', 'feature flag', 'release train', 'semantic versioning', 'changelog', 'migration'.

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Provides GitOps best practices for ArgoCD, Flux, Argo Rollouts, and progressive delivery strategies. Use when setting up GitOps workflows, configuring continuous delivery, managing Kubernetes deployments declaratively, or when user mentions 'gitops', 'argocd', 'flux', 'progressive delivery', 'reconciliation', 'argo rollouts', 'canary', 'sealed secrets'.

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[Deprecated] quality gate now covers tests + canary. Use `cm-quality-gate` instead.

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Uses AWS CloudWatch SDK (boto3) to configure anomaly detection bands on metrics via PutAnomalyDetector API. Integrates with SNS for notifications and CloudWatch Synthetics for canary-based uptime monitoring.

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Orchestrates deployment pipelines using the Argo Workflows Engine API and Argo CD ApplicationSet controller. Implements progressive delivery with Argo Rollouts canary and blue-green strategies.

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Configure Kubernetes Ingress networking with NGINX Ingress Controller, cert-manager for automated TLS certificate management, path-based routing, rate limiting, and multi-domain hosting with SSL termination and load balancing. Use when exposing multiple Kubernetes services via a single load balancer, implementing path-based or host-based routing, automating TLS certificate issuance with Let's Encrypt, or setting up blue-green and canary deployments with traffic splitting.

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houtu-dependencies enterprise-grade Spring Cloud microservice foundational framework complete usage guide. GroupId is io.github.lujiafa, covering unified response, exception handling, parameter parsing, session authentication, permission control, signature verification, anti-replay, distributed lock, rate limiting, database field encryption, config decryption, access logging, canary routing, weighted load balancing, Feign enhancement, Sentinel circuit breaking, service discovery, Swagger documentation, crypto utilities, HTTP client, monitoring metrics, and other enterprise-grade capabilities. When the project build file (pom.xml or build.gradle/build.gradle.kts) contains io.github.lujiafa or houtu-related dependencies, or when the user mentions houtu or houtu-dependencies, this Skill must be read and code must be generated strictly following framework conventions. Even if the user is simply doing regular Spring Boot development (e.g., writing Controller, Service, Feign), as long as the project includes houtu, the houtu approach must be used instead of native Spring. When the user explicitly wants to use the houtu framework and the project has not yet included it, proactively add the BOM and required Starters; when the project already includes it, proactively identify and import required module dependencies based on business scenarios during coding, naturally integrating framework capabilities to enhance business services based on business semantics, rather than waiting for the user to specify each one.

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Detects code quality vulnerabilities in mobile apps (Android/iOS). Trigger on: SQL injection in SQLite, JavaScript injection in WebViews, intent injection, unsafe deserialization, NSKeyedUnarchiver, NSCoding, Java serialization, Parcelable, buffer overflow, JNI native code, PIE disabled, NX disabled, stack canary absent, RELRO, ARC disabled, third-party library CVE, vulnerable dependency, outdated SDK, targetSdkVersion, update enforcement missing, implicit Intent, URL loading in WebView, object persistence, memory corruption, OWASP dependency check. Covers MASVS-CODE-1/2/3/4.

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Format string exploitation playbook. Use when printf-family functions receive user-controlled format strings, enabling arbitrary stack reads (%p/%s), arbitrary memory writes (%n/%hn/%hhn), GOT/hook overwrites, and canary/libc/PIE leaks.

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Binary protection bypass playbook. Use when identifying and bypassing ASLR, PIE, NX/DEP, stack canary, RELRO, FORTIFY_SOURCE, CET, and MTE protections in ELF binaries to enable exploitation.

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Helper for release operations, compilation of changelogs between tags, version lockstep syncing, and promotion of GitHub releases from canary/pre-release to latest/production. Use when the user asks to "compile the changelog", "promote release to latest", "tag a release", or do version release operations.

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Canonical go-live checklist for Agentforce deployments with rehearsed rollback and stakeholder sign-off records. NOT for the technical pre-prod verification behind those sign-off rows — cost telemetry, rate limits, canary rollout, latency benchmarks — use agentforce/agentforce-production-readiness-checklist. NOT for general Salesforce release management — use devops/release-management.

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An Agentforce agent is moving from build or sandbox to live end-user traffic and the team needs a comprehensive readiness gate: coverage testing, Trust Layer config, guardrails, cost telemetry, observability, rate limits, permissions, rollout strategy, rollback plan, performance benchmarks. Triggers: 'we want to ship our Agentforce agent next week', 'pre-prod readiness review for our Service Agent', 'what do we need before turning the agent on for real customers', 'agent went live and is hallucinating, what should we have caught', 'cost monitoring for our internal sales agent', 'rollout strategy from internal pilot to GA'. NOT for the lighter five-block activation sign-off artifact — use agentforce/agent-deployment-checklist. NOT for authoring the guardrails themselves — use agentforce/agentforce-guardrails. NOT for building the test harness — use agentforce/agentforce-eval-harness. NOT for Trust Layer feature setup in isolation — use agentforce/einstein-trust-layer.

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Experimental/manual harness canary procedure. It records benchmark manifests and scores but does not provide a fully automated runner.

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Decompose systems into microservices and apply canonical distributed-systems patterns. Use this skill whenever the user wants to split a monolith into services, design service boundaries, choose between microservices and a modular monolith, implement sagas or the outbox pattern, set up CQRS or event sourcing, configure an API gateway or BFF, add resilience (circuit breakers, retries, timeouts), or implement distributed tracing with OpenTelemetry. Also trigger for distributed transactions, service discovery, event-driven architecture, contract testing with Pact, canary releases, and idempotent consumers.

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Test egress and DLP controls using synthetic canary data across authorized exfiltration channels.

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