“queue”的搜索结果

Audits a Cloudflare application repository for code paths and configuration that may create usage-based billing exposure. Use when asked to inspect Cloudflare Worker, D1, Durable Objects, storage, queue, or compute usage for unexpected bills, billing risks, or cost drivers. Reports evidence and uncertainty. Runs offline by default; optionally correlates user-authorized, bounded evidence from existing official tools. Does not guarantee a spending cap.

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Comment-archaeology sweep - find work items hiding in TODO/FIXME/for-now comments and plan-doc ledgers, judge them, file issues, queue trivial fixes. Good idle-loop activity.

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Operate Aavegotchi Gotchiverse player workflows on Base mainnet (8453): alchemica channeling, surveying and harvesting, crafting installations/tiles, building on parcels (equip/unequip/move/batch equip), installation upgrades, craft/upgrade queue management, and parcel access-right management. Use when interacting with Realm/Installation/Tile diamonds via subgraph-first discovery and onchain verification/execution with Foundry cast.

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Turn a short natural-language request into a bounded work contract (intent, scope, acceptance, initial queue) without asking for code or architecture review.

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Catalog APIs, persistence models, and message/event payloads into DATA_MODEL.md at the project root. Use after implementation when a diff touches request/response types, schemas, ORM models, queue payloads, or webhook shapes. Triggers on "document data model", "update DATA_MODEL", "catalog API shapes".

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Use when building data pipelines, ETL jobs, event processors, message-broker producers/consumers, application caching layers, database migrations, BigQuery queries, or event-sourcing handlers in TypeScript. Triggers on edits to indexer/ETL/migration code, Prisma or Drizzle schemas, BigQuery integration code, RabbitMQ/Kafka/SQS/BullMQ producer or consumer code, Redis cache wrappers, or mentions of "data engineering", "ETL", "pipeline", "indexer", "event sourcing", "data warehouse", "data migration", "message queue", "RabbitMQ", "Kafka", "SQS", "BullMQ", "Redis cache", or "caching".

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Build or review dygo durable Jobs, Job Executions, queues, workers, retries, idempotency, and Schedules. Use for background or recurring business work.

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Design and operate Azure Storage services for durability, performance, and secure access. Use this skill when users ask about Blob, Files, Queues, Tables, or Data Lake storage patterns. Covers redundancy, tiering, access models, lifecycle policies, and compliance.

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Design Kafka consumer groups that survive rebalances, hit the right delivery guarantee (at-most/at-least/exactly-once), and handle poison messages without stalling the topic. Use when picking a partition assignment strategy (Range vs Sticky vs Cooperative-Sticky vs the new KIP-848 protocol), tuning heartbeat / session / max.poll.interval timeouts, choosing manual vs auto offset commits, designing dead-letter or retry topics, or migrating from Classic to the next-gen Consumer protocol. NOT for Kafka cluster ops (broker tuning, partition reassignment), schema design (Avro/Protobuf/Schema Registry), or stream processing topology (use a kafka-streams skill).

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Wave-based parallel scheduling for DAG execution. Manages execution order, resource allocation, and parallelism constraints. Activate on 'schedule dag', 'execution waves', 'parallel scheduling', 'task queue', 'resource allocation'. NOT for building DAGs (use dag-graph-builder) or actual execution (use dag-parallel-executor).

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Agent system design patterns distilled from the OpenClaw codebase. Gateway-centric control, Session Key hierarchy, Binding routing, Lane Queue concurrency, Sub-agent Spawn+Announce, 4-tier automation, Plugin architecture, Policy Chain, Failover strategies. Triggered by "gateway", "session", "binding", "lane", "spawn", "announce", "heartbeat", "cron", "hook", "plugin", "policy", "failover" keywords.

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Scan every open pull request in a GitHub repository, filter to the ones that are genuinely mergeable now, and report a compact verdict with a suggested merge order. Use when the user asks which PRs can be merged, wants an open-PR backlog triaged or reviewed in bulk, asks why a PR is blocked, or wants to clear a queue of stale or bot-reviewed PRs.

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Checks the canonical upstream issue tracker, discussion forums, and open pull requests, merge requests, or equivalent change queues for existing reports, discussion, or work on a problem just discussed. Use before diagnosing, fixing, or reporting an apparent open-source problem to avoid duplicate effort and missed context.

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Review every Beads issue waiting on a person, one at a time, using the interactive questionnaire UI rather than plain-text prompts. Use when asked to go through blockers, clear the human queue, answer beads waiting on the user, triage `bd human list`, or unblock agent work that needs a decision.

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Grind through ready beads in priority order by running several issues at once, each in its own isolated git worktree managed by worktrunk (`wt`), then merging the finished branches back one at a time. Use when asked to work the beads queue in parallel, to run N issues concurrently, or when a serial grind is too slow and the ready issues are independent.

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Grind through ready beads serially in priority order, one at a time in the current worktree, without stopping between issues. Use when asked to work the beads queue, grind the backlog, keep working through ready issues, or make unattended progress overnight. For concurrent worktrees instead, use beads-parallel-grinding.

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AWS serverless and event-driven architecture expert based on Well-Architected Framework. Use when building serverless APIs, Lambda functions, REST APIs, microservices, or async workflows. Covers Lambda with TypeScript/Python, API Gateway (REST/HTTP), DynamoDB, Step Functions, EventBridge, SQS, SNS, and serverless patterns. Essential when user mentions serverless, Lambda, API Gateway, event-driven, async processing, queues, pub/sub, or wants to build scalable serverless applications with AWS best practices.

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Set up a parallel agent team for COMPLEX tasks: creates worktree structure, an ownership map, and an initialized task queue. Use when a task is decomposed into parallel subtasks.

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JIRA Service Management via jira-as: service desks, requests, customers, orgs, queues, SLAs, approvals. Requires JSM tenant + agent role. NOT core issue ops (mk:jira-issue) or admin (mk:jira-admin).

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Fetch external sources (web / arXiv / GitHub) and turn them into scanner-gated wiki CANDIDATES — never canonical pages. Every fetched byte is DATA; url-guarded, size-capped, redirect-re-validated, injection-scanned, and secret-scrubbed before a candidate is even created. Requires network. NOT for capturing local knowledge (see mk:wiki); NOT for one-shot page-to-markdown (see mk:web-to-markdown).

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Develop, challenge, and document Chisel processor microarchitecture designs before implementation. Use when discussing or writing design documents for processor pipelines, queues, issue logic, rename, ROB, LSU, caches, MSHRs, forwarding, wakeup, replay, flush, privilege, exceptions, or other cycle-accurate hardware mechanisms; when converting design conversations into stable Markdown specifications; or when reviewing a proposed Chisel CPU design for correctness, timing, area, verification cost, and cross-document consistency.

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Diagnose and optimize timing-critical Chisel RTL for FPGA implementation while preserving cycle semantics. Use for Vivado timing bottlenecks, long ready or admission paths, queue and issue selection, free-list bank mapping, priority encoders, one-hot arbitration, wide muxes, late-arriving forwarding or override data, high-fanout controls, cross-module predicates, register-boundary changes, emitted-Verilog inspection, or routed-DCP A/B analysis. Also use when a source-level simplification needs proof that it changes timing without changing architectural state.

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Spotify: play, search, queue, manage playlists and devices.

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Use when adding auth, webhooks, uploads, queues, secrets, tenant boundaries, or public endpoints — produces trust boundaries + abuse cases mapped to files, BEFORE implementation.

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