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Found 25 Skills
Use the Geti application end to end through its REST API — the project → dataset → annotate → train → deploy pipeline served by the FastAPI backend in `application/backend/`. Use when a user (not a contributor) wants to create a project, upload media, add annotations, launch a training or quantization job, track job status, configure a source → model → sink inference pipeline, and enable live inference. Covers the `/api/...` endpoints and the async job model, not backend code changes.
Elastic ML anomaly detection skill — investigation/RCA, score explanation, job operations (create, datafeed, start/stop, results), and troubleshooting (missing docs, memory limits, datafeed health, lifecycle). Operates against Kibana Agent Builder MCP tools (`ad_*`) on `.ml-anomalies-*`, `.ml-config`, `.ml-notifications-*`, `.ml-annotations-*`. Use when answering "what broke?"/"which entity?"/RCA, "why is score high/low?"/renormalization, "datafeed stopped"/"memory limit", or any request to set up or configure an ML anomaly detection job.
Create and manage Elastic ML anomaly detection jobs via the API. Use when setting up jobs on an index or data stream, configuring jobs and datafeeds, or opening, starting, or stopping them.
自主调度技能 — 管理周期任务、去重、触发窗口与执行状态。
Run, monitor, analyze, and debug LLM evaluations via nemo-evaluator-launcher. Covers running evaluations, checking status and live progress, debugging failed runs, exporting artifacts and logs, and analyzing results. ALWAYS triggers on mentions of running evaluations, checking progress, debugging failed evals, analyzing or analysing runs or results, run directories or artifact paths on clusters, Slurm job issues, invocation IDs, or inspecting logs (client logs, server logs, SSH to cluster, tail logs, grep logs). Do NOT use for creating or modifying evaluation configs.
Create, manage, and review Eve jobs, phases, and dependencies. Use when running knowledge work in Eve or structuring job hierarchies.
Manage GPU compute jobs on the Qizhi (启智) platform using qzcli — a kubectl-style CLI tool. Use when user says "qzcli", "启智平台", "submit job", "stop job", "查计算组", "avail", "list jobs", "batch submit", or needs to manage distributed training jobs on a Qizhi instance.
Skills to interact with your Dataproc clusters and jobs.
Create and manage Alibaba Cloud IMS video translation jobs via OpenAPI (subtitle/voice/face). Use when you need API-based video translation, status polling, and job management.
Data Mask end-to-end operation on a sandbox: configure a masking policy over PII, run the masking job, poll it to completion, report masked-record results, and abort an in-progress run. Use when the user needs to run, monitor, or cancel a Salesforce Data Mask job, mask PII/sandbox data, or work with DataMaskPolicy / DataMaskPolicyJobRun. TRIGGER when: user runs a data mask job, masks sandbox PII, polls masking status, reports masked records, or aborts a running mask. DO NOT TRIGGER when: writing anonymization Apex by hand (use platform-apex-generate), generating test data (use platform-data-manage), or deploying unrelated metadata (use platform-metadata-deploy).
Alibaba Cloud E-HPC Instant Computing Platform Job Management Toolkit, supporting operations such as creation/submission, query, detail retrieval, log query, and deletion of E-HPC Instant (EHPC Instant/ehpcinstant) jobs. It is used when users need to create jobs, query job lists, get job details, delete jobs, or query job logs.
Launch and manage batch jobs on Lightning AI - run commands on cloud CPUs/GPUs from a Docker image or a Studio snapshot, monitor status, fetch logs, SSH into a running job or multi-machine worker, collect artifacts, and run multi-machine (distributed) training. Use when the user wants to run training, data processing, or any batch workload on lightning.ai, or asks to SSH into a job / MMT.