709 skills · sorted by relevance
Process one recommendation selected by ID from a local issue or CI triage report. Apply, reject, or defer it, record the outcome, and obtain separate confirmation before each change made on GitHub.
Build Laravel applications with authenticated APIs, interactive interfaces, and background jobs. The skill guides database relationships, query optimization, and feature tests, using tools such as Sanctum for authentication and Livewire for interfaces.
Review open issues and discussions to create a clear work queue. Record the five highest-priority items, suggested labels, possible duplicates, and cases needing human judgment in a state file for future reviews.
Look up exact syntax, options, JSON output, defaults, and error meanings for a known OpenRig command. Use the reference to check command behavior and diagnose runtime differences against the installed help and running daemon.
Set up an OpenRig team for ongoing repository work, with clear ownership, implementation, independent review, and handoffs. Choose direct coordination, a task queue, or an explicit workflow, then expand the team as authorized work requires.
Coordinate work across an OpenRig agent team with clear assignments, attached context, completion criteria, and selected review checkpoints. Track queue status, identify blocked or idle owners, and resolve handoff gaps while leaving implementation with the assigned agents.
Develop and deploy Cloudflare Workers, manage related storage and services, and troubleshoot configuration with Wrangler. The skill checks official documentation and configuration definitions before preparing commands, with guidance for local development, environments, secrets, and logs.
Model ongoing requests and multi-step agent work to estimate capacity, latency, and cost per completed task. Break execution into stages, account for queues and retries, and produce workload tables with average and peak resource budgets.
Review pull requests at a specific commit using existing discussions, review plans, and executed checks. Produce a detailed Chinese review and a concise English verdict, then publish and read back the result to confirm its contents.
Find the relevant architectural guidance for API design, security, cloud infrastructure, message queues, and caching. This skill acts as an index to specialized references and lists principles for structuring software, distributed systems, and access controls.
Add OpenTelemetry tracing to frontend and backend flows. Connect execution records across services and background jobs, record phase durations and entity IDs, and mark failures so developers can investigate slow or broken operations.
Queue open microsoft/apm pull requests (community fixes, PRs without an issue, or PRs that close an issue) and fan them out through an isolated pool (default 2) of autopilot-pr-triage-worker sessions. Advisory only. Never merges, never assigns, never requests reviewers, never runs autopilot-pr-review-worker. Activate on a mixed PR list or queue-open when the job is PR triage. Works in a local session, Copilot App automation, Cloud Agent, Remote Agent, or Agentic Workflow.
The English summary is being prepared. Showing the original description.
Queue open microsoft/apm issues and fan them out through an isolated pool (default 2) of autopilot-issue-triage-worker sessions. Advisory only. Never implements, never assigns, never requests reviewers. Activate on a mixed issue list or queue-all when the job is triage. Works in a local session, Copilot App automation, Cloud Agent, Remote Agent, or Agentic Workflow.
The English summary is being prepared. Showing the original description.
Use this skill to implement ONE microsoft/apm issue already selected by autopilot-issue-delivery-scheduler. Queue signal is `status/accepted` or a named bounded accept; that is not permission. Requires fresh human-scope evidence from scripts/governance before any mutate. May reproduce a bug, implement the accepted change, and open a fix PR. Not a queue manager and not a triage scheduler. Works in the scheduler's session, a child session, Cloud Agent, Remote Agent, or Agentic Workflow.
The English summary is being prepared. Showing the original description.
Use this skill when the user is doing hands-on NVMe-over-Fabrics storage-target work on a BlueField DPU or ConnectX NIC with DOCA STA — standing up a doca_sta DOCA Core context that accelerates the target-side NVMe-oF data path over RDMA, defining doca_sta_subsystem targets (NQN + namespaces) backed by local NVMe-PCI backend disks (doca_sta_be), checking device support via doca_sta_cap_is_supported, sizing the per-connection I/O queues, or debugging DOCA_ERROR_* from a STA call. Trigger even when the user does not say "DOCA STA" — typical implicit phrasings include "my NVMe-oF Connect never completes", "Identify Controller times out over RoCE", "16 I/O queues at depth 1024 — does this BlueField support that", "offload the nvmf target onto the DPU", or "DOCA_ERROR_IO_FAILED on an NVMe read". Refuse and route elsewhere for DOCA install, raw RDMA data movement, raw packet I/O, flow-rule programming, or initiator-side / host NVMe stack work — those belong to other skills.
The English summary is being prepared. Showing the original description.
Operate the DOCA UROM Service container on BlueField Arm for remote memory operations (puts, gets, atomics, collectives) enqueued by a paired host using `doca-urom`: pull the NGC image, choose the UCX component, size queues, configure Comch pairing, and align host and service versions. SECURITY: the service has no standalone access control; Comch pairing and RDMA permissions are the boundary. Pair only intended hosts, expose least-privilege memory regions, and verify both views before start. Trigger for slow UCX collectives, unexpected NOT_PERMITTED, or missing completions. Do not use for host application code, MPI/UCX integration design, or DOCA install.
The English summary is being prepared. Showing the original description.
DOCA Rivermax (doca_rmax) receive streams for timing-precise media over IP (SMPTE ST 2110 video / audio, market data, scientific feeds) on a BlueField DPU or ConnectX host, once the Rivermax SDK and its license are installed; getting the SDK or license is doca-setup / doca-public-knowledge-map territory. Trigger on "ST 2110 receive isn't getting frames", "sub-microsecond jitter on my media receiver", "NOT_SUPPORTED from doca_rmax_init", "no recv events after stream start", or "license check failing on a media receiver", even without naming Rivermax. Covers doca_rmax_in_stream sessions, the SDK + license precondition check, doca_rmax_get_*_supported capability queries, pairing with doca-eth queues and doca-flow steering, and DOCA_ERROR_* from Rivermax calls. Refuse and route elsewhere for programming the underlying queue (doca-eth), steering rules (doca-flow), PTP / clock sync (doca-firefly), or best-effort packet I/O.
The English summary is being prepared. Showing the original description.
Use this skill for hands-on DOCA GPI programming — wiring a GPU-Packet-Initiator context so a CUDA kernel drives RDMA queues directly from GPU memory without host CPU mediation. Covers picking GPI vs doca-gpunetio, the doca_gpi / domain / channel object model, the GPU-side handle handoff (doca_gpu_gpi_channel*), attaching GPU memory to a GPI domain, the domain and channel attribute objects, and debugging DOCA_ERROR_* from doca_gpi_* calls. Trigger even when the user does not explicitly mention "DOCA GPI" — implicit phrasings include "my CUDA kernel needs to post RDMA directly from GPU memory", "DOCA_ERROR_* from doca_gpi_gpu_channel_get", "how do I hand a GPU handle to my CUDA kernel", "how many channels can a GPI domain hold", or "GPU kernel driving RDMA without the host CPU on the path". Refuse and route elsewhere for the doca-gpunetio Send/Receive surface, the doca-rdma queue lifecycle, DPA-side initiation (doca-rdmi), or the CUDA programming model — those belong to other skills.
The English summary is being prepared. Showing the original description.
Azure Storage Services including Blob Storage, File Shares, Queue Storage, Table Storage, and Data Lake. Answers questions about storage access tiers (hot, cool, cold, archive), when to use each tier, and tier comparison. Provides object storage, SMB file shares, async messaging, NoSQL key-value, and big data analytics. Includes lifecycle management. USE FOR: blob storage, file shares, queue storage, table storage, data lake, upload files, download blobs, storage accounts, access tiers, storage tiers, hot cool cold archive, storage tier comparison, when to use storage tiers, lifecycle management, Azure Storage concepts. DO NOT USE FOR: SQL databases, Cosmos DB (use azure-prepare), messaging with Event Hubs or Service Bus (use azure-messaging).
The English summary is being prepared. Showing the original description.
Azure Service Bus SDK for Python messaging. Use for queues, topics, subscriptions, and enterprise messaging patterns. Triggers: "service bus", "ServiceBusClient", "queue", "topic", "subscription", "message broker".
The English summary is being prepared. Showing the original description.
Use when the user asks to "build our social crisis protocol", "mentions are exploding — what do we do first", or "when do we pause the posting queue"; produces a 1-5 severity ladder with tunable Estimated trigger thresholds (mention-velocity multiples vs the 7-day listening baseline, sentiment flip, journalist/regulator contact, employee-conduct class), the first-mechanical-action rule — pause ALL scheduled posts AND paid amplification, with dated state markers dropped to the channels proposal protocol and reconciled post-incident — a pre-approved holding-statement library with committed update cadences, when-NOT-to-post rules, a spokesperson/approval matrix, and a post-crisis retro template; re-runs the social-quality-auditor pre-publish gate before un-pausing the queue. Not for email deliverability incidents (blocklist, spam-rate spikes) — use deliverability-qa; inside a launch window launch-day-conductor owns incident handling. 社媒危机预案/暂停队列/声明库/发言人矩阵
The English summary is being prepared. Showing the original description.
Auto-grow a pro-workflow wiki by running a budget-capped BFS research loop over pluggable source fetchers (web, arXiv, GitHub). Each iteration pops a seed from the queue, fetches sources, drafts a wiki page, dedupes claims against existing pages, enqueues follow-up seeds. Halts on budget cap, depth cap, or convergence. Use when the user says "research <topic>", "grow the <slug> wiki", "auto-research", or wants a knowledge base that builds itself overnight.
The English summary is being prepared. Showing the original description.
Routes serverless requests to a compute form factor and the skill that owns it. Applies first to Lambda, API Gateway, EventBridge, Step Functions and event-driven work while the compute, orchestration or integration choice is open — API backends, webhooks, jobs, cron, queue/stream consumers, durable workflows, event routing, Step Functions vs Durable Functions, and Pipes vs native event source mappings for queues and streams. Decides Event Functions on-demand vs Managed Instances, Web Functions, MicroVMs, EventBridge rules/Scheduler/Pipes/bus, HTTP vs REST API. Owns shared Lambda references (cold starts, SnapStart, concurrency, event sources, function URLs, throttling, troubleshooting). Defers to the specialized skill once a request commits to one form factor or service, or describes its defining feature, even unnamed (durable checkpointing and automatic step retries, Firecracker sandbox, managed instances, Node.js server). Not for EC2, ECS/EKS/Fargate or Amplify hosting.
The English summary is being prepared. Showing the original description.
Notion-as-source-of-truth dispatch board for running your work like an AI agency. One Tasks database is the source of truth; tasks flow Suggestion through Discussion, To-Do, In Progress, and Done with subtasks, recurring cadences, dependencies, and template subtrees. Batch execution fans approved To-Do rows out to parallel agents with per-task model selection. Use when capturing chat to Notion, running the To-Do queue, suggesting, approving, or discussing tasks, or coordinating multi-task batches. Trigger with "/agency-os" subcommands or natural-language variants ("add a suggestion: …", "let's discuss X", "run the queue").
The English summary is being prepared. Showing the original description.