[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"org-arize":3,"repo-skills-v-0-3-0":124},{"org":4,"repos":54},{"slug":5,"name":6,"logoUrl":7,"githubOrg":8,"website":9,"skillCount":10,"repoCount":11,"topRepos":12,"topTags":22,"lastUpdatedAt":53},"arize","Arize AI","https:\u002F\u002Fpexgzepcugksgbtrxkhf.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Forg-logos\u002Farize.jpg","Arize-ai","https:\u002F\u002Farize.com",23,3,[13,16,19],{"name":14,"skillCount":15},"Arize-ai\u002Farize-skills",13,{"name":17,"skillCount":18},"Arize-ai\u002Fphoenix",8,{"name":20,"skillCount":21},"Arize-ai\u002Farize-claude-code-plugin",2,[23,26,29,32,35,38,41,44,47,50],{"slug":24,"name":25},"llm","LLM",{"slug":27,"name":28},"observability","Observability",{"slug":30,"name":31},"evals","Evals",{"slug":33,"name":34},"datasets","Datasets",{"slug":36,"name":37},"tracing","Tracing",{"slug":39,"name":40},"analytics","Analytics",{"slug":42,"name":43},"cli","CLI",{"slug":45,"name":46},"data-analysis","Data Analysis",{"slug":48,"name":49},"debugging","Debugging",{"slug":51,"name":52},"testing","Testing","2026-07-31T05:58:09.13624",[55,83,109],{"name":56,"fullName":14,"repoUrl":57,"skillCount":15,"stars":58,"forks":59,"description":60,"topics":61,"topTags":70,"topTagCount":81,"lastUpdatedAt":82},"arize-skills","https:\u002F\u002Fgithub.com\u002FArize-ai\u002Farize-skills",38,5,"Agent skills for Arize — datasets, experiments, and traces via the ax CLI",[62,63,64,5,65,66,67,33,68,69,36],"agent-skills","ai-agents","ai-observability","claude-code","codex","cursor","experiments","llmops",[71,72,73,74,75,78],{"slug":24,"name":25},{"slug":27,"name":28},{"slug":30,"name":31},{"slug":39,"name":40},{"slug":76,"name":77},"anthropic","Anthropic",{"slug":79,"name":80},"audit","Audit",25,"2026-07-31T05:53:45.56562",{"name":84,"fullName":17,"repoUrl":85,"skillCount":18,"stars":86,"forks":87,"description":88,"topics":89,"topTags":101,"topTagCount":108,"lastUpdatedAt":53},"phoenix","https:\u002F\u002Fgithub.com\u002FArize-ai\u002Fphoenix",10513,977,"AI Observability & Evaluation",[90,91,64,92,76,33,30,93,94,95,96,69,97,98,99,100],"agents","ai-monitoring","aiengineering","langchain","llamaindex","llm-eval","llm-evaluation","llms","openai","prompt-engineering","smolagents",[102,103,104,105,106,107],{"slug":30,"name":31},{"slug":24,"name":25},{"slug":27,"name":28},{"slug":51,"name":52},{"slug":36,"name":37},{"slug":45,"name":46},10,{"name":110,"fullName":20,"repoUrl":111,"skillCount":21,"stars":112,"forks":113,"description":114,"topics":115,"topTags":116,"topTagCount":113,"lastUpdatedAt":123},"arize-claude-code-plugin","https:\u002F\u002Fgithub.com\u002FArize-ai\u002Farize-claude-code-plugin",20,4,"Arize Claude Code Plugin",[],[117,118,121,122],{"slug":42,"name":43},{"slug":119,"name":120},"data-engineering","Data Engineering",{"slug":33,"name":34},{"slug":27,"name":28},"2026-07-12T08:08:07.341667",{"items":125,"total":15},[126,141,158,168,188,199,209,219,227,236,246,261,276],{"slug":127,"name":127,"fn":128,"description":129,"org":130,"tags":131,"stars":58,"repoUrl":57,"updatedAt":140},"arize-admin","manage Arize enterprise user access","Manages Arize users, organizations, spaces, projects, roles, role bindings, resource restrictions, and API keys via the ax CLI. Use for enterprise admin workflows: inviting and offboarding users, onboarding new teams, creating custom roles for SAML\u002FSSO mappings, assigning roles to users, restricting project-level access, and managing service keys for multi-tenant architectures. Covers ax users, ax organizations, ax spaces, ax projects, ax roles, ax role-bindings, and ax api-keys.",{"slug":5,"name":6,"logoUrl":7,"githubOrg":8},[132,134,137],{"name":43,"slug":42,"type":133},"tag",{"name":135,"slug":136,"type":133},"Operations","operations",{"name":138,"slug":139,"type":133},"Permissions","permissions","2026-07-22T05:37:21.991338",{"slug":142,"name":142,"fn":143,"description":144,"org":145,"tags":146,"stars":58,"repoUrl":57,"updatedAt":157},"arize-ai-provider-integration","manage Arize AI provider integrations","Creates, reads, updates, and deletes Arize AI integrations that store LLM provider credentials used by evaluators and other Arize features. Supports any LLM provider (e.g. OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, Vertex AI, Gemini, NVIDIA NIM). Use when the user mentions AI integration, LLM provider credentials, create integration, list integrations, update credentials, delete integration, or connecting an LLM provider to Arize.",{"slug":5,"name":6,"logoUrl":7,"githubOrg":8},[147,148,151,154,155],{"name":77,"slug":76,"type":133},{"name":149,"slug":150,"type":133},"Azure","azure",{"name":152,"slug":153,"type":133},"Integrations","integrations",{"name":25,"slug":24,"type":133},{"name":156,"slug":98,"type":133},"OpenAI","2026-07-22T05:37:23.90468",{"slug":159,"name":159,"fn":160,"description":161,"org":162,"tags":163,"stars":58,"repoUrl":57,"updatedAt":167},"arize-annotation","manage Arize annotation workflows","Creates and manages annotation configs (categorical, continuous, freeform label schemas) and annotation queues (human review workflows) on Arize. Applies human annotations to project spans via the Python SDK. Use when the user mentions annotation config, annotation queue, label schema, human feedback, bulk annotate spans, update_annotations, labeling queue, annotate record, or human review.",{"slug":5,"name":6,"logoUrl":7,"githubOrg":8},[164,165,166],{"name":46,"slug":45,"type":133},{"name":25,"slug":24,"type":133},{"name":28,"slug":27,"type":133},"2026-07-22T05:37:19.010776",{"slug":169,"name":169,"fn":170,"description":171,"org":172,"tags":173,"stars":58,"repoUrl":57,"updatedAt":187},"arize-compliance-audit","audit AI agents for regulatory compliance","INVOKE THIS SKILL when auditing an AI agent or LLM app for regulatory compliance. Covers EU AI Act, GPAI Code of Practice, GDPR, NIST AI RMF, Colorado AI Act, HIPAA, and ISO 42001. Scans the codebase for compliance gaps, cross-references Arize instrumentation for audit trail coverage, and produces an actionable remediation checklist tailored to the selected frameworks.",{"slug":5,"name":6,"logoUrl":7,"githubOrg":8},[174,175,178,181,184],{"name":80,"slug":79,"type":133},{"name":176,"slug":177,"type":133},"Compliance","compliance",{"name":179,"slug":180,"type":133},"GDPR","gdpr",{"name":182,"slug":183,"type":133},"Legal","legal",{"name":185,"slug":186,"type":133},"Security","security","2026-07-19T05:39:42.632738",{"slug":189,"name":189,"fn":190,"description":191,"org":192,"tags":193,"stars":58,"repoUrl":57,"updatedAt":198},"arize-dataset","manage Arize datasets and examples","Creates, manages, and queries Arize datasets and examples. Covers dataset CRUD, appending examples, exporting data, and file-based dataset creation using the ax CLI. Use when the user needs test data, evaluation examples, or mentions create dataset, list datasets, export dataset, append examples, dataset version, golden dataset, or test set.",{"slug":5,"name":6,"logoUrl":7,"githubOrg":8},[194,195,196,197],{"name":120,"slug":119,"type":133},{"name":34,"slug":33,"type":133},{"name":31,"slug":30,"type":133},{"name":25,"slug":24,"type":133},"2026-07-22T05:37:20.943718",{"slug":200,"name":200,"fn":201,"description":202,"org":203,"tags":204,"stars":58,"repoUrl":57,"updatedAt":208},"arize-evaluator","configure and run Arize evaluations","Handles LLM-as-judge and code evaluator workflows on Arize including creating\u002Fupdating evaluators, running evaluations on spans or experiments, managing tasks, trigger-run operations, column mapping, and continuous monitoring. Use when the user mentions create evaluator, LLM judge, code evaluator, hallucination, faithfulness, correctness, relevance, run eval, score spans, score experiment, trigger-run, column mapping, continuous monitoring, or improve evaluator prompt.",{"slug":5,"name":6,"logoUrl":7,"githubOrg":8},[205,206,207],{"name":31,"slug":30,"type":133},{"name":25,"slug":24,"type":133},{"name":28,"slug":27,"type":133},"2026-07-25T05:32:37.552903",{"slug":210,"name":210,"fn":211,"description":212,"org":213,"tags":214,"stars":58,"repoUrl":57,"updatedAt":218},"arize-experiment","run and analyze Arize experiments","Creates, runs, and analyzes Arize experiments for evaluating and comparing model performance. Covers experiment CRUD, exporting runs, comparing results, and evaluation workflows using the ax CLI. Use when the user mentions create experiment, run experiment, compare models, model performance, evaluate AI, experiment results, benchmark, A\u002FB test models, or measure accuracy.",{"slug":5,"name":6,"logoUrl":7,"githubOrg":8},[215,216,217],{"name":40,"slug":39,"type":133},{"name":31,"slug":30,"type":133},{"name":25,"slug":24,"type":133},"2026-07-31T05:53:44.725539",{"slug":220,"name":220,"fn":221,"description":222,"org":223,"tags":224,"stars":58,"repoUrl":57,"updatedAt":82},"arize-instrumentation","instrument LLM applications with Arize AX","Adds Arize AX tracing to an LLM application for the first time. Detects the stack, routes to the single matching integration doc, wires auto-instrumentation after user confirmation, and verifies traces land. Use when the user wants to instrument their app, add tracing from scratch, set up LLM observability, integrate OpenTelemetry or openinference, or get started with Arize tracing.",{"slug":5,"name":6,"logoUrl":7,"githubOrg":8},[225,226],{"name":25,"slug":24,"type":133},{"name":28,"slug":27,"type":133},{"slug":228,"name":228,"fn":229,"description":230,"org":231,"tags":232,"stars":58,"repoUrl":57,"updatedAt":235},"arize-link","generate deep links to Arize resources","Generates deep links to the Arize UI for traces, spans, sessions, datasets, labeling queues, evaluators, and annotation configs. Produces clickable URLs for sharing Arize resources with team members. Use when the user wants to link to or open a trace, span, session, dataset, evaluator, or annotation config in the Arize UI.",{"slug":5,"name":6,"logoUrl":7,"githubOrg":8},[233,234],{"name":40,"slug":39,"type":133},{"name":28,"slug":27,"type":133},"2026-07-12T08:07:50.568982",{"slug":237,"name":237,"fn":238,"description":239,"org":240,"tags":241,"stars":58,"repoUrl":57,"updatedAt":245},"arize-prompt-optimization","optimize LLM prompts with Arize","Optimizes, improves, and debugs LLM prompts using production trace data, evaluations, and annotations. Extracts prompts from spans, gathers performance signal, and runs a data-driven optimization loop using the ax CLI. Use when the user mentions optimize prompt, improve prompt, make AI respond better, improve output quality, prompt engineering, prompt tuning, or system prompt improvement.",{"slug":5,"name":6,"logoUrl":7,"githubOrg":8},[242,243,244],{"name":31,"slug":30,"type":133},{"name":25,"slug":24,"type":133},{"name":28,"slug":27,"type":133},"2026-07-22T05:37:22.946231",{"slug":247,"name":247,"fn":248,"description":249,"org":250,"tags":251,"stars":58,"repoUrl":57,"updatedAt":260},"arize-prompts","manage prompt templates in Arize","INVOKE THIS SKILL for Arize Prompt Hub and `ax prompts` workflows: author or import templates and save (Workflows A–B), label\u002Fpromote (C), or list\u002Fget\u002Fedit\u002Fdelete\u002Fduplicate (D). Use when the user mentions ax prompts, Prompt Hub, creating\u002Fediting\u002Fsaving a prompt, `{variable}` placeholders, or production\u002Fstaging labels. For improving prompt text using traces or eval scores, use arize-prompt-optimization. For running experiments, use arize-experiment.",{"slug":5,"name":6,"logoUrl":7,"githubOrg":8},[252,255,256,257],{"name":253,"slug":254,"type":133},"Automation","automation",{"name":31,"slug":30,"type":133},{"name":25,"slug":24,"type":133},{"name":258,"slug":259,"type":133},"Management","management","2026-07-22T05:37:27.052909",{"slug":262,"name":262,"fn":263,"description":264,"org":265,"tags":266,"stars":58,"repoUrl":57,"updatedAt":275},"arize-span-routing","route OpenTelemetry spans to Arize","Use when one Python service must send each agent's, tenant's, team's, or request's spans to its correct Arize space and project using application metadata. Covers dynamic OpenTelemetry routing for custom agent builders and multi-tenant applications, including register_with_routing, set_routing_context, multi-space tracing, and custom span routing.",{"slug":5,"name":6,"logoUrl":7,"githubOrg":8},[267,268,271,274],{"name":28,"slug":27,"type":133},{"name":269,"slug":270,"type":133},"OpenTelemetry","opentelemetry",{"name":272,"slug":273,"type":133},"Python","python",{"name":37,"slug":36,"type":133},"2026-07-25T05:56:28.16608",{"slug":277,"name":277,"fn":278,"description":279,"org":280,"tags":281,"stars":58,"repoUrl":57,"updatedAt":285},"arize-trace","export and inspect Arize traces","Downloads, exports, and inspects existing Arize traces and spans to understand what an LLM app is doing or debug runtime issues. Covers exporting traces by ID, spans by ID, sessions by ID, and root-cause investigation using the ax CLI. Use when the user wants to look at existing trace data, see what their LLM app is doing, export traces, download spans, investigate errors, or analyze behavior regressions.",{"slug":5,"name":6,"logoUrl":7,"githubOrg":8},[282,283,284],{"name":49,"slug":48,"type":133},{"name":25,"slug":24,"type":133},{"name":28,"slug":27,"type":133},"2026-07-31T05:53:43.588527"]