253 个 · 按相关度排序
Runs HTTP load tests with gradually increasing concurrent connections. It measures response-time percentiles, throughput, and errors, identifies where performance starts to deteriorate, and recommends a concurrency level based on the results.
中文简介正在准备中。当前显示英语简介。
Inspect and adjust how many BB threads can run at once, globally or on a specific host. Pause new work with a zero limit, remove the global cap, or restore processor-based automatic host limits.
中文简介正在准备中。当前显示英语简介。
Build an implementation queue from accepted GitHub issues and distribute them to dedicated workers. Record selection reasons, check for existing pull requests, and process the full queue with a configurable concurrency limit, defaulting to two workers.
中文简介正在准备中。当前显示英语简介。
Organize pull request reviews by selecting eligible labeled or explicitly named requests and distributing them to a dedicated worker pool. It records selection decisions and limits concurrent reviews, with two worker sessions by default.
中文简介正在准备中。当前显示英语简介。
Select open pull requests for initial classification and distribute them to dedicated workers with a concurrency limit. Record why each request is included or excluded, without merging changes, assigning owners, or requesting reviewers.
中文简介正在准备中。当前显示英语简介。
Use this skill when concurrent requests, async tasks, threads, workers, goroutines, or agents need independent NeMo Relay scope stacks and correct ancestry propagation.
中文简介正在准备中。当前显示原文说明。
Functional programming helpers for Golang using samber/lo — 500+ type-safe generic functions for slices, maps, channels, strings, math, tuples, and concurrency (Map, Filter, Reduce, GroupBy, Chunk, Flatten, Find, Uniq, etc.). Core immutable package (lo), concurrent variants (lo/parallel aka lop), in-place mutations (lo/mutable aka lom), lazy iterators (lo/it aka loi for Go 1.23+), and experimental SIMD (lo/exp/simd). Apply when using or adopting samber/lo, when the codebase imports github.com/samber/lo, or when implementing functional-style data transformations in Go. Not for streaming pipelines (→ See `samber/cc-skills-golang@golang-samber-ro` skill).
中文简介正在准备中。当前显示原文说明。
Defensive Golang coding against accidental bugs — nil panics, typed-nil interfaces, `append` backing-array aliasing, silent int64-to-int32 truncation, float `==` comparison, `defer` inside loops, defensive copies of slices and maps, and usable zero values. Use when a Go program panics on a nil map write or nil pointer dereference, when reviewing code for nil-safety, numeric conversion overflow, or resource lifecycle, or when designing a type whose zero value must be safe. Not for designing concurrent access with goroutines, channels, or sync primitives (→ See `samber/cc-skills-golang@golang-concurrency` skill), not for exploitable vulnerabilities such as injection, weak crypto, or leaked secrets (→ See `samber/cc-skills-golang@golang-security` skill), and not for debugging an already-failing program (→ See `samber/cc-skills-golang@golang-troubleshooting` skill).
中文简介正在准备中。当前显示原文说明。
Golang concurrency design — goroutine lifecycle and leak prevention, channels and `select`, channel ownership and direction, `sync.Mutex`/`RWMutex`/`sync.Map`/`sync.Once`/atomics, `errgroup`, `singleflight`, worker pools, and fan-out/fan-in pipelines. Use when writing or reviewing concurrent Go code, when choosing between channels and mutexes, when protecting a shared map or counter, or when a goroutine has no clear exit. Not for defensive coding unrelated to concurrency such as nil panics, slice aliasing, or numeric overflow (→ See `samber/cc-skills-golang@golang-safety` skill), and not for debugging a specific hung, crashing, or racing program after the fact (→ See `samber/cc-skills-golang@golang-troubleshooting` skill).
中文简介正在准备中。当前显示原文说明。
Apply when concurrent actors might write to the same file, branch, key, or state object. Eliminate the sharing first; serialize structurally only when one shared writer is a real invariant.
中文简介正在准备中。当前显示原文说明。
Apply before writing logic: choosing core types and data structures, sequencing scaffold-vs-feature work, asking what concurrent actors share. Get the data structures right so downstream code becomes obvious.
中文简介正在准备中。当前显示原文说明。
Evaluates, configures, and migrates workloads to AWS Lambda Managed Instances (LMI). Runs Lambda Event Functions (standard Lambda) on EC2 instances in the user's account while AWS manages provisioning, patching, scaling, routing, and load balancing. Triggers when queries mention Lambda Managed Instances, LMI, capacity providers, multi-concurrent execution environments, EC2-backed Lambda, persistent Lambda instances, PerExecutionEnvironmentMaxConcurrency, CapacityProviderConfig, cold start elimination via dedicated instances, migrating Lambda Event Functions to managed instances, or cost comparison between Lambda Event Functions and LMI with Savings Plans or Reserved Instances. Also covers long-running and asynchronous workloads and the 90-minute (5400s) function timeout for asynchronous and event-source-mapping (SQS, Kinesis, DynamoDB Streams / ESM) invocations, including how to raise the function timeout up to 90 minutes / 5400s and the related duration limits.
中文简介正在准备中。当前显示原文说明。
Deploys, queries, and debugs AWS Marketplace usage-based (PAYG) metering — the pipeline (ResolveCustomer, BatchMeterUsage, EventBridge via SAM) and querying/debugging metering records, statuses, failures, discrepancies. Covers Concurrent Agreements (CustomerAWSAccountId + LicenseArn), multi-product, CloudTrail Event History (90 days; never CloudTrail Lake), Seller Reports (Billed Revenue/Usage columns + CSV/SDDS parsing), existing-stack detection, metering region for BatchMeterUsage/MeterUsage (DisabledApiException), metered AMI/Container + IAM roles, where registration data lives (customer-profile table), legacy ProductCode + CustomerIdentifier, DuplicateRecord/CustomerNotSubscribed, bad LicenseArn. Also SCOPES adjacent asks — flat-rate/SaaS-Subscription "do I still meter", CCP included-units + overage, contract term/annual renewal, forecasting future bills/usage — with the right answer or a one-line redirect. Use for any BatchMeterUsage/ResolveCustomer or SaaS usage-billing question.
中文简介正在准备中。当前显示原文说明。
Race condition and TOCTOU testing for web apps. Use when testing one-time operations, concurrent HTTP abuse, rate-limit bypass, Turbo Intruder gates, HTTP/2 single-packet attacks, and CWE-362-style synchronization gaps.
中文简介正在准备中。当前显示原文说明。
Design scalable distributed systems using structured approaches for load balancing, caching, database scaling, and message queues. Use when the user mentions "system design", "scale this", "high availability", "rate limiter", "design a URL shortener", "design Twitter", "design Uber", "design a news feed", "system design interview", "capacity planning", or "distributed architecture". Also trigger when estimating infrastructure requirements, choosing between microservices and monoliths, or designing for millions of concurrent users. Covers common system designs (TinyURL, feeds, chat) and back-of-the-envelope estimation. For data fundamentals, see ddia-systems. For resilience, see release-it.
中文简介正在准备中。当前显示原文说明。
Apply before writing logic: choosing core types and data structures, sequencing scaffold-vs-feature work, asking what concurrent actors share. Get the data structures right so downstream code becomes obvious.
中文简介正在准备中。当前显示原文说明。
Apply when concurrent actors might write to the same file, branch, key, or state object. Eliminate the sharing first; serialize structurally only when one shared writer is a real invariant.
中文简介正在准备中。当前显示原文说明。
Resolve conflicts and merges when several branches are open against one repo at the same time — the hotspot files every change must touch (registry manifests, a single version field, shared tool config, one aggregated test module, tracked build output), union-vs-recompute-vs-rebuild as three different correct resolutions, generated artifacts that must never be merged, non-deterministic serialization that makes every branch conflict, renumbered identifiers that git cannot show you, and why a clean auto-merge is not a passing test. Use when rebasing or merging a long-lived branch, resolving conflict markers, reviewing a merge commit, deciding what a repo should commit vs generate, or setting up a repo that will take parallel contributions.
中文简介正在准备中。当前显示原文说明。
Swift 6.2 可接近的并发性 — 默认单线程，@concurrent 用于显式后台卸载，隔离一致性用于主 actor 类型。
中文简介正在准备中。当前显示原文说明。
Swift 6.2 易用的并发（Approachable Concurrency）—— 默认单线程，使用 @concurrent 进行显式后台卸载，针对主执行角色（Main Actor）类型的隔离一致性。
中文简介正在准备中。当前显示原文说明。
Use this skill for planning, testing, and safely executing PostgreSQL schema migrations — especially when working with production data or shared databases. **Trigger when user asks to:** - Test a schema migration before applying it to production - Add, remove, or rename columns safely on a live table - Change a column's data type without downtime - Add or drop indexes, constraints, or foreign keys on large tables - Understand which ALTER TABLE operations lock the table - Roll back a failed migration - Plan a zero-downtime migration strategy - Fork a database to test a migration safely **Keywords:** migration, schema change, ALTER TABLE, add column, drop column, rename column, change type, zero downtime, lock, AccessExclusiveLock, concurrent index, forking, rollback, backfill, deploy Covers: lock-level reference for every common DDL operation, safe migration patterns, fork-based testing, zero-downtime column changes, index creation, constraint addition, backfill strategies, pre/post-migration validation, and rollback planning.
中文简介正在准备中。当前显示原文说明。
Transform sequential Python code into parallel/concurrent implementations. Use when asked to parallelize Python code, improve code performance through concurrency, convert loops to parallel execution, or identify parallelization opportunities. Handles CPU-bound (multiprocessing), I/O-bound (asyncio, threading), and data-parallel (vectorization) scenarios.
中文简介正在准备中。当前显示原文说明。
Use when erlang's concurrency model including lightweight processes, message passing, process links and monitors, error handling patterns, selective receive, and building massively concurrent systems on the BEAM VM.
中文简介正在准备中。当前显示原文说明。
Parallel research agent orchestration dispatching 5-10 concurrent agents for comprehensive multi-source research with synthesis and validation.
中文简介正在准备中。当前显示原文说明。