Guided journey from a shipped app that works but feels rough to a product that fits the job, flows without friction, reads clearly, and persuades honestly. Orchestrates nine skills phase by phase - jobs-to-be-done, ux-heuristics, design-everyday-things, refactoring-ui, microinteractions, made-to-stick, influence-psychology, high-perf-browser, steve-jobs-design-review - asking the user questions at every decision point and recording results in the project docs/ folder (CUSTOMER.md, DESIGN.md, POSITIONING.md, IMPROVE-APP-PLAN.md) so the journey resumes across sessions. Use when the user wants to fix a clunky product, cut UX friction, sharpen in-app copy, or says 'the app works but feels rough'. Not for code, tests, or hardening - use improve-code-quality (fresh prototype) or remove-technical-debt (aged); no app yet, create-app; needs growth loops, grow-app; marketing-site friction, improve-website; one leaking flow, conversion-optimization. For one framework in isolation, invoke that skill directly.

Triage current Meshtastic-Android crashes in Firebase Crashlytics — establish the right version filter (topVersions first, then topIssues filtered to "X.Y.Z (versionCode)"), fan out one crash-investigator subagent per top issue in parallel, and return a distilled verdict table. Use for "what's crashing", "triage Crashlytics", or "is build NNNN healthy" sweeps; for a single known issue id, dispatch crash-investigator directly instead.

Use when weighing whether to extract a shared abstraction, base class, interface, or generic helper versus keeping code duplicated; evaluating DRY tradeoffs across parallel Sonarr and Radarr implementations, Refit or other code-generated API clients, OpenAPI/gRPC/GraphQL DTOs, or anti-corruption layers over distinct external systems; reviewing a PR that introduces a new shared abstraction spanning independent bounded contexts; considering unwinding a wrong abstraction back into duplicated copies. Triggers on phrases like "should I abstract this", "extract a base class", "these look duplicated", "DRY this up", "unify Sonarr and Radarr", "refactor to share", "rule of three", "wrong abstraction". Do NOT use for mechanical refactors within a single type or for trivial helper extraction inside one module.

Configures CI/CD pipelines using AWS CodePipeline, CodeBuild, CodeDeploy, CodeConnections, and CodeArtifact. Covers CodePipeline V2 (triggers, variables, execution modes, cross-account), buildspec.yml (caching, VPC, Docker), CodeDeploy strategies (blue/green, canary, linear), CodeArtifact (private package registries, auth tokens, cross-account), and source connections (GitHub, GitLab, Bitbucket). Applies when CodePipeline, CodeBuild, CodeDeploy, CodeConnections, CodeArtifact, buildspec.yml, appspec.yml, or CI/CD pipeline orchestration is referenced. Does NOT cover: ECS Fargate services or task definitions (use aws-containers), CDK Pipelines or cdk deploy (use aws-cdk), sam deploy (use aws-serverless), Amplify deployments (use aws-amplify), or GitHub Actions/GitLab CI.

Runs SQL analytics on SageMaker Catalog asset metadata tables exported as Apache Iceberg in S3 Tables. Covers governance queries, asset growth tracking, ownership audits, time-travel over catalog state, and metadata quality analysis. Applies when querying catalog inventory, finding assets without descriptions, comparing catalog snapshots, or auditing data ownership. Trigger phrases: catalog inventory SQL, how many assets, assets without descriptions, asset growth over time, who owns this data, catalog governance, data quality audit, catalog analytics.

Configures CI/CD pipelines using AWS CodePipeline, CodeBuild, CodeDeploy, CodeConnections, and CodeArtifact. Covers CodePipeline V2 (triggers, variables, execution modes, cross-account), buildspec.yml (caching, VPC, Docker), CodeDeploy strategies (blue/green, canary, linear), CodeArtifact (private package registries, auth tokens, cross-account), and source connections (GitHub, GitLab, Bitbucket). Applies when CodePipeline, CodeBuild, CodeDeploy, CodeConnections, CodeArtifact, buildspec.yml, appspec.yml, or CI/CD pipeline orchestration is referenced. Does NOT cover: ECS Fargate services or task definitions (use aws-containers), CDK Pipelines or cdk deploy (use aws-cdk), sam deploy (use aws-serverless), Amplify deployments (use aws-amplify), or GitHub Actions/GitLab CI.

Provisions, connects, migrates, and operates Amazon RDS for Db2. Applies when provisioning with IBM customer and site IDs (License Manager, BYOL, GovCloud), connecting over TLS, fixing SQL30082N after Secrets Manager rotation, migration from Db2 LUW (Linux, AIX, Windows, AS400) or z/OS mainframe (ADB2GEN, Q Replication), choosing code page/collation (EBCDIC, CCSID), S3 backup/restore, Multi-AZ and cross-region standby replicas, RDSADMIN procedures, customer-managed KMS BYOK, self-managed Active Directory Kerberos, Db2 audit to S3, minimum IAM, or colocation.

Selects, investigates, and compares AWS object, file, and block storage services, and answers cost, performance, configuration, security, and troubleshooting questions about storage services. Applies when a user asks where to store or archive data based on their usage patterns; which storage service to choose or how two compare; how to migrate data from on-premises or between AWS services; how to protect, replicate, or recover data; how to optimize storage costs; where to deploy shared NFS, SMB, or POSIX file systems; where to store vector embeddings or tabular data; what storage backs enterprise file shares, self-managed databases on EC2, VMware, or stateful containers; or asks what an AWS storage service can do or how it works. Relevant for storage needs for workloads such as AI/ML, analytics, EDA, HPC, media, genomics, or financial trading. Not applicable for SQL query engines (Athena, Spark, Redshift, EMR), ETL (Glue), streaming (Kafka, MSK, Kinesis), or managed database services (RDS, Aurora, DynamoDB).

Run an AWS Security Agent scan on the workspace — uploads the source to AWS, scans it with the managed Security Agent service, and returns ranked, verified findings with code locations and remediations. Use when the user asks to scan code, find vulnerabilities, run a security scan or review, check security issues, check scan status, show findings, list recent scans, or stop a scan.

Configure AWS Security Agent for the current workspace — provision or reuse an agent space, IAM service role, and S3 bucket. Use when the user asks to "set up security agent", "configure security scanner", "is security agent configured", or on first-time use before any scan or pentest.

Use when a developer wants to create a new agent project or get started with AgentCore. Handles framework selection, project scaffolding, first deploy, and first invocation. Triggers on: "build an agent", "create an agent", "get started", "new project", "agentcore create", "which framework", "Strands vs LangGraph", "hello world agent", "first agent", "create MCP server", "host MCP server", "agentcore dev", "dev server", "what port", "local development". Not for adding capabilities to existing projects — use agents-build or agents-connect. Strands vs LangGraph in a migration context routes to agents-build, not here. Connecting to an existing MCP server routes to agents-connect, not here.

Set up and author a documentation site with @lobehub/docs-kit (the `lobedocs` CLI, React Router + Vite static docs used by ui.lobehub.com). Covers consumer repo layout, docs.config.ts, package scripts, component doc pages (index.mdx frontmatter, `?demo` imports, <Demo>, <Api>), guide pages, home page, changelog, and the build-time validations that reject bad docs. Trigger on docs-kit, lobedocs, defineDocsConfig, docs.config.ts, migrate from dumi, write component docs, add a demo, <Demo>, <Api>, index.mdx, 文档站, 写文档, 组件文档, 迁移 dumi.

Compose a product or documentation home page from the @lobehub/ui/awesome landing components: LandingHero, AgentSkillCard, LogoMarquee, LandingSection, BentoGrid/BentoCard, CodeShowcase, FeatureGrid, InstallBanner and FluidGradient. Covers page structure, the lobedocs homePage hook, router links, theming the accent gradient, and a review checklist. Trigger on build a home page, landing page, docs home, marketing page, hero section, redesign home, lobedocs homePage, 首页, 落地页, 官网首页.

Create, modify, debug, and deploy Apify Actors, and write their input and output schemas. Use when building an Actor from scratch, changing or troubleshooting Actor code, generating or updating .actor schema files, or pushing an Actor to the Apify platform. To wrap an existing non-Actor project, use apify-actorization instead.

Review a completed, paused, or blocked coding-agent session to identify friction, mistakes, near misses, missing context, and opportunities to improve future work. Use when the user asks to wrap up, run a retrospective, explain what issues the agent faced, capture lessons learned, or recommend improvements to repository instructions, documentation, skills, tooling, tests, or workflows. Produce an evidence-based, propose-only report; do not apply follow-up changes unless the user asks.

Search and recall relevant memories from past sessions via memsearch. Use when the user's question could benefit from historical context, past decisions, debugging notes, previous conversations, or project knowledge -- especially questions like 'what did I decide about X', 'why did we do Y', or 'have I seen this before'. Also use when you see `[memsearch] Recall available if needed` capability hints injected via SessionStart or UserPromptSubmit. Typical flow: search for 3-5 chunks, expand the most relevant, optionally deep-drill into original transcripts via the anchor format. Skip when the question is purely about current code state (use Read/Grep), ephemeral (today's task only), or the user has explicitly asked to ignore memory.

UI snapshot cache (display-only, main-thread) + unified startup timing schema — cold-start reads from snapshot namespaces (MMKV on native, IndexedDB on web) and the cross-platform `[StartupTiming]` log taxonomy. Use when adding or debugging a UI snapshot / SWR cache, debugging startup performance regressions, analyzing cold start timeline, or comparing iOS vs Android startup phases. Triggers on: ui snapshot cache, SnapshotCache, swr cache, usePromiseResult cache, cold start, startup optimization, 启动时间, SSR hydration, Balance displayed regression, contextAtomBase, flushColdStartCache, __ONEKEY_CTX_ATOM_SNAPSHOT__, StartupTiming, main_host.did_start, bg_runner.start.

Runs a declarative strategy spec over OHLCV bars with the manifoldbt Rust engine, pairs the fill log into round trips, and emits the eight inputs the backtest-expert skill scores. Use when the user wants to execute a backtest, measure a rule they have described, obtain win rate / average win / average loss / max drawdown from real bars, or feed backtest-expert with measured numbers instead of estimates.

解释 BK-CI 流水线或创作流的 Model JSON，帮助 AI 理解 Model -> Stage -> Container(Job) -> Element 的含义、启动参数、矩阵、Finally、审核与常见插件语义。用户贴出流水线 JSON、创作流 JSON、编排数据，或询问某个 Stage/Job/插件/atomCode/stepId 含义时使用。

Inverse-fold a backbone with ligand, nucleic-acid, and metal context using LigandMPNN (Dauparas et al. 2023, github.com/dauparas/LigandMPNN). Reach for this skill to redesign the residues lining a binding pocket around a bound small molecule or cofactor, to design metal-coordinating sites where the geometry must be respected, or to get threaded designed-sequence PDBs out of any MPNN run.