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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.\nmetadata:\n  author: arize\n  version: \"1.0\"\n---\n\n# Arize Link\n\nGenerate deep links to the Arize UI for traces, spans, sessions, datasets, labeling queues, evaluators, and annotation configs.\n\n## When to Use\n\n- User wants a link to a trace, span, session, dataset, labeling queue, evaluator, or annotation config\n- You have IDs from exported data or logs and need to link back to the UI\n- User asks to \"open\" or \"view\" any of the above in Arize\n\n## Required Inputs\n\nCollect from the user or context (exported trace data, parsed URLs):\n\n| Always required | Resource-specific |\n|---|---|\n| `org_id` (base64) | `project_id` + `trace_id` [+ `span_id`] — trace\u002Fspan |\n| `space_id` (base64) | `project_id` + `session_id` — session |\n| | `dataset_id` — dataset |\n| | `queue_id` — specific queue (omit for list) |\n| | `evaluator_id` [+ `version`] — evaluator |\n\n**All path IDs must be base64-encoded** (characters: `A-Za-z0-9+\u002F=`). A raw numeric ID produces a valid-looking URL that 404s. If the user provides a number, ask them to copy the ID directly from their Arize browser URL (`https:\u002F\u002Fapp.arize.com\u002Forganizations\u002F{org_id}\u002Fspaces\u002F{space_id}\u002F…`). If you have a raw internal ID (e.g. `Organization:1:abC1`), base64-encode it before inserting into the URL.\n\n## URL Templates\n\nBase URL: `https:\u002F\u002Fapp.arize.com` (override for on-prem)\n\n**Trace** (add `&selectedSpanId={span_id}` to highlight a specific span):\n```\n{base_url}\u002Forganizations\u002F{org_id}\u002Fspaces\u002F{space_id}\u002Fprojects\u002F{project_id}?selectedTraceId={trace_id}&queryFilterA=&selectedTab=llmTracing&timeZoneA=America%2FLos_Angeles&startA={start_ms}&endA={end_ms}&envA=tracing&modelType=generative_llm\n```\n\n**Session:**\n```\n{base_url}\u002Forganizations\u002F{org_id}\u002Fspaces\u002F{space_id}\u002Fprojects\u002F{project_id}?selectedSessionId={session_id}&queryFilterA=&selectedTab=llmTracing&timeZoneA=America%2FLos_Angeles&startA={start_ms}&endA={end_ms}&envA=tracing&modelType=generative_llm\n```\n\n**Dataset** (`selectedTab`: `examples` or `experiments`):\n```\n{base_url}\u002Forganizations\u002F{org_id}\u002Fspaces\u002F{space_id}\u002Fdatasets\u002F{dataset_id}?selectedTab=examples\n```\n\n**Queue list \u002F specific queue:**\n```\n{base_url}\u002Forganizations\u002F{org_id}\u002Fspaces\u002F{space_id}\u002Fqueues\n{base_url}\u002Forganizations\u002F{org_id}\u002Fspaces\u002F{space_id}\u002Fqueues\u002F{queue_id}\n```\n\n**Evaluator** (omit `?version=…` for latest):\n```\n{base_url}\u002Forganizations\u002F{org_id}\u002Fspaces\u002F{space_id}\u002Fevaluators\u002F{evaluator_id}\n{base_url}\u002Forganizations\u002F{org_id}\u002Fspaces\u002F{space_id}\u002Fevaluators\u002F{evaluator_id}?version={version_url_encoded}\n```\nThe `version` value must be URL-encoded (e.g., trailing `=` → `%3D`).\n\n**Annotation configs:**\n```\n{base_url}\u002Forganizations\u002F{org_id}\u002Fspaces\u002F{space_id}\u002Fannotation-configs\n```\n\n## Time Range\n\nCRITICAL: `startA` and `endA` (epoch milliseconds) are **required** for trace\u002Fspan\u002Fsession links — omitting them defaults to the last 7 days and will show \"no recent data\" if the trace falls outside that window.\n\n**Priority order:**\n1. **User-provided URL** — extract and reuse `startA`\u002F`endA` directly.\n2. **Span `start_time`** — pad ±1 day (or ±1 hour for a tighter window).\n3. **Fallback** — last 90 days (`now - 90d` to `now`).\n\nPrefer tight windows; 90-day windows load slowly.\n\n## Instructions\n\n1. Gather IDs from user, exported data, or URL context.\n2. Verify all path IDs are base64-encoded.\n3. Determine `startA`\u002F`endA` using the priority order above.\n4. Substitute into the appropriate template and present as a clickable markdown link.\n\n## Troubleshooting\n\n| Problem | Solution |\n|---|---|\n| \"No data\" \u002F empty view | Trace outside time window — widen `startA`\u002F`endA` (±1h → ±1d → 90d). |\n| 404 | ID wrong or not base64. Re-check `org_id`, `space_id`, `project_id` from the browser URL. |\n| Span not highlighted | `span_id` may belong to a different trace. Verify against exported span data. |\n| `org_id` unknown | `ax` CLI doesn't expose it. 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",{"type":49,"tag":135,"props":700,"children":702},{"className":701},[],[703],{"type":54,"value":516},{"type":54,"value":562},{"type":49,"tag":135,"props":706,"children":708},{"className":707},[],[709],{"type":54,"value":524},{"type":54,"value":711}," (±1h → ±1d → 90d).",{"type":49,"tag":109,"props":713,"children":714},{},[715,720],{"type":49,"tag":131,"props":716,"children":717},{},[718],{"type":54,"value":719},"404",{"type":49,"tag":131,"props":721,"children":722},{},[723,725,730,732,737,738,743],{"type":54,"value":724},"ID wrong or not base64. Re-check ",{"type":49,"tag":135,"props":726,"children":728},{"className":727},[],[729],{"type":54,"value":140},{"type":54,"value":731},", ",{"type":49,"tag":135,"props":733,"children":735},{"className":734},[],[736],{"type":54,"value":187},{"type":54,"value":731},{"type":49,"tag":135,"props":739,"children":741},{"className":740},[],[742],{"type":54,"value":151},{"type":54,"value":744}," from the browser URL.",{"type":49,"tag":109,"props":746,"children":747},{},[748,753],{"type":49,"tag":131,"props":749,"children":750},{},[751],{"type":54,"value":752},"Span not highlighted",{"type":49,"tag":131,"props":754,"children":755},{},[756,761],{"type":49,"tag":135,"props":757,"children":759},{"className":758},[],[760],{"type":54,"value":173},{"type":54,"value":762}," may belong to a different trace. Verify against exported span data.",{"type":49,"tag":109,"props":764,"children":765},{},[766,776],{"type":49,"tag":131,"props":767,"children":768},{},[769,774],{"type":49,"tag":135,"props":770,"children":772},{"className":771},[],[773],{"type":54,"value":140},{"type":54,"value":775}," unknown",{"type":49,"tag":131,"props":777,"children":778},{},[779,785,787,792],{"type":49,"tag":135,"props":780,"children":782},{"className":781},[],[783],{"type":54,"value":784},"ax",{"type":54,"value":786}," CLI doesn't expose it. Ask user to copy from ",{"type":49,"tag":135,"props":788,"children":790},{"className":789},[],[791],{"type":54,"value":292},{"type":54,"value":793},".",{"type":49,"tag":63,"props":795,"children":797},{"id":796},"related-skills",[798],{"type":54,"value":799},"Related Skills",{"type":49,"tag":70,"props":801,"children":802},{},[803],{"type":49,"tag":74,"props":804,"children":805},{},[806,811,813,818,819,824,826,831],{"type":49,"tag":272,"props":807,"children":808},{},[809],{"type":54,"value":810},"arize-trace",{"type":54,"value":812},": Export spans to get ",{"type":49,"tag":135,"props":814,"children":816},{"className":815},[],[817],{"type":54,"value":159},{"type":54,"value":731},{"type":49,"tag":135,"props":820,"children":822},{"className":821},[],[823],{"type":54,"value":173},{"type":54,"value":825},", and ",{"type":49,"tag":135,"props":827,"children":829},{"className":828},[],[830],{"type":54,"value":583},{"type":54,"value":793},{"type":49,"tag":63,"props":833,"children":834},{"id":392},[835],{"type":54,"value":836},"Examples",{"type":49,"tag":57,"props":838,"children":839},{},[840,842,848],{"type":54,"value":841},"See ",{"type":49,"tag":843,"props":844,"children":846},"a",{"href":845},"references\u002FEXAMPLES.md",[847],{"type":54,"value":845},{"type":54,"value":849}," for a complete set of concrete URLs for every link type.",{"items":851,"total":960},[852,868,890,902,924,940,950],{"slug":853,"name":853,"fn":854,"description":855,"org":856,"tags":857,"stars":20,"repoUrl":21,"updatedAt":867},"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":8,"name":9,"logoUrl":10,"githubOrg":11},[858,861,864],{"name":859,"slug":860,"type":16},"CLI","cli",{"name":862,"slug":863,"type":16},"Operations","operations",{"name":865,"slug":866,"type":16},"Permissions","permissions","2026-07-22T05:37:21.991338",{"slug":869,"name":869,"fn":870,"description":871,"org":872,"tags":873,"stars":20,"repoUrl":21,"updatedAt":889},"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":8,"name":9,"logoUrl":10,"githubOrg":11},[874,877,880,883,886],{"name":875,"slug":876,"type":16},"Anthropic","anthropic",{"name":878,"slug":879,"type":16},"Azure","azure",{"name":881,"slug":882,"type":16},"Integrations","integrations",{"name":884,"slug":885,"type":16},"LLM","llm",{"name":887,"slug":888,"type":16},"OpenAI","openai","2026-07-22T05:37:23.90468",{"slug":891,"name":891,"fn":892,"description":893,"org":894,"tags":895,"stars":20,"repoUrl":21,"updatedAt":901},"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":8,"name":9,"logoUrl":10,"githubOrg":11},[896,899,900],{"name":897,"slug":898,"type":16},"Data Analysis","data-analysis",{"name":884,"slug":885,"type":16},{"name":14,"slug":15,"type":16},"2026-07-22T05:37:19.010776",{"slug":903,"name":903,"fn":904,"description":905,"org":906,"tags":907,"stars":20,"repoUrl":21,"updatedAt":923},"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":8,"name":9,"logoUrl":10,"githubOrg":11},[908,911,914,917,920],{"name":909,"slug":910,"type":16},"Audit","audit",{"name":912,"slug":913,"type":16},"Compliance","compliance",{"name":915,"slug":916,"type":16},"GDPR","gdpr",{"name":918,"slug":919,"type":16},"Legal","legal",{"name":921,"slug":922,"type":16},"Security","security","2026-07-19T05:39:42.632738",{"slug":925,"name":925,"fn":926,"description":927,"org":928,"tags":929,"stars":20,"repoUrl":21,"updatedAt":939},"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":8,"name":9,"logoUrl":10,"githubOrg":11},[930,933,935,938],{"name":931,"slug":932,"type":16},"Data Engineering","data-engineering",{"name":934,"slug":32,"type":16},"Datasets",{"name":936,"slug":937,"type":16},"Evals","evals",{"name":884,"slug":885,"type":16},"2026-07-22T05:37:20.943718",{"slug":941,"name":941,"fn":942,"description":943,"org":944,"tags":945,"stars":20,"repoUrl":21,"updatedAt":949},"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":8,"name":9,"logoUrl":10,"githubOrg":11},[946,947,948],{"name":936,"slug":937,"type":16},{"name":884,"slug":885,"type":16},{"name":14,"slug":15,"type":16},"2026-07-25T05:32:37.552903",{"slug":951,"name":951,"fn":952,"description":953,"org":954,"tags":955,"stars":20,"repoUrl":21,"updatedAt":959},"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":8,"name":9,"logoUrl":10,"githubOrg":11},[956,957,958],{"name":18,"slug":19,"type":16},{"name":936,"slug":937,"type":16},{"name":884,"slug":885,"type":16},"2026-07-31T05:53:44.725539",13,{"items":962,"total":1081},[963,977,986,998,1010,1020,1032,1042,1053,1059,1067,1073],{"slug":964,"name":964,"fn":965,"description":966,"org":967,"tags":968,"stars":974,"repoUrl":975,"updatedAt":976},"annotate-spans","annotate LLM spans and traces","Write effective, consistent annotations on LLM\u002Fagent spans and traces, and coach the user on annotation practice. Load this whenever you are about to record structured feedback with the `batch_span_annotate` tool, or when the user asks how to annotate, label, score, or review spans\u002Ftraces, build a failure taxonomy, or set up human\u002FLLM review. Do NOT load for: pure analysis with no intent to save feedback (use debug-trace), latency or cost statistics, or prompt authoring (use playground).\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[969,970,971,972],{"name":936,"slug":937,"type":16},{"name":884,"slug":885,"type":16},{"name":14,"slug":15,"type":16},{"name":973,"slug":35,"type":16},"Tracing",10513,"https:\u002F\u002Fgithub.com\u002FArize-ai\u002Fphoenix","2026-07-12T08:08:14.140984",{"slug":32,"name":32,"fn":978,"description":979,"org":980,"tags":981,"stars":974,"repoUrl":975,"updatedAt":985},"reason about Phoenix dataset structure","Understand what a Phoenix dataset is and reason well about its examples, outputs, splits, and how it feeds evaluators and experiments. Load this whenever a dataset is in view or the user asks what a dataset is, how splits work, what an output \"means\", or how datasets relate to experiments and evals. This skill governs the judgment; any tool descriptions govern the mechanics.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[982,983,984],{"name":897,"slug":898,"type":16},{"name":934,"slug":32,"type":16},{"name":936,"slug":937,"type":16},"2026-07-12T08:08:21.695457",{"slug":987,"name":987,"fn":988,"description":989,"org":990,"tags":991,"stars":974,"repoUrl":975,"updatedAt":997},"debug-trace","diagnose failures using trace investigation","Diagnose failure modes by systematically investigating traces. Trigger when the user explicitly asks for cross-trace diagnosis: \"what's going wrong?\", \"were there errors?\", \"debug this\", \"where is my agent struggling?\". Do NOT trigger on: (1) advice questions (\"what should I do?\"), (2) statistical questions (\"what's the average latency?\"), (3) summarize requests, (4) trace filtering (\"show me traces with errors\"), (5) vague questions (\"is there a problem?\"), (6) unrelated requests.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[992,995,996],{"name":993,"slug":994,"type":16},"Debugging","debugging",{"name":14,"slug":15,"type":16},{"name":973,"slug":35,"type":16},"2026-07-12T08:08:10.44243",{"slug":999,"name":999,"fn":1000,"description":1001,"org":1002,"tags":1003,"stars":974,"repoUrl":975,"updatedAt":1009},"evaluators","author and refine Phoenix evaluators","Author or refine a Phoenix evaluator — code or LLM-as-a-judge — that scores a run's output. Trigger when the user wants to create a new evaluator, improve an existing one's logic or rubric, choose labels, or decide what to measure on a dataset or experiment. Do NOT trigger on: (1) manual prompt drafting (use `playground`), (2) running or comparing experiments themselves (use `experiments`), (3) cross-trace failure diagnosis with no evaluator in scope (use `debug-trace`).\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[1004,1005,1006],{"name":936,"slug":937,"type":16},{"name":884,"slug":885,"type":16},{"name":1007,"slug":1008,"type":16},"Testing","testing","2026-07-31T05:58:09.13624",{"slug":33,"name":33,"fn":1011,"description":1012,"org":1013,"tags":1014,"stars":974,"repoUrl":975,"updatedAt":1019},"run and compare dataset-backed experiments","Run, read, and compare dataset-backed experiments to find evidence that a prompt or pipeline is improving. Trigger when the user wants to iterate over a dataset with experiments, compare experiment runs, read experiment quality\u002Flatency\u002Fcost, or decide whether a change actually helped. Running a prompt over a dataset is implicitly an experiment — load this skill when dataset-backed work begins, before authoring evaluators for the experiment and before starting the recorded run, not only when reading results. Do NOT trigger on: (1) manual prompt drafting with no dataset-backed evaluation in scope (use `playground`), (2) authoring or refining an evaluator's logic or rubric (use `evaluators`), (3) cross-trace failure diagnosis with no experiment in scope (use `debug-trace`).\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[1015,1016,1017,1018],{"name":934,"slug":32,"type":16},{"name":936,"slug":937,"type":16},{"name":884,"slug":885,"type":16},{"name":1007,"slug":1008,"type":16},"2026-07-12T08:08:11.691477",{"slug":1021,"name":1021,"fn":1022,"description":1023,"org":1024,"tags":1025,"stars":974,"repoUrl":975,"updatedAt":1031},"phoenix-graphql","query Phoenix API with GraphQL","Write efficient GraphQL queries against the Phoenix API. Load this skill in two cases: (1) before composing any non-trivial GraphQL query yourself for data analysis (via the `phoenix-gql` bash command) — it contains schema entrypoints and patterns that eliminate the need for introspection; (2) when the user asks for help writing GraphQL queries for their own scripts, tools, or integrations against Phoenix — it covers the endpoint, authentication, and client examples.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[1026,1027,1028],{"name":18,"slug":19,"type":16},{"name":897,"slug":898,"type":16},{"name":1029,"slug":1030,"type":16},"GraphQL","graphql","2026-07-12T08:08:17.163493",{"slug":1033,"name":1033,"fn":1034,"description":1035,"org":1036,"tags":1037,"stars":974,"repoUrl":975,"updatedAt":1041},"playground","author and iterate on prompts in Phoenix","Author, edit, or iterate on prompts in the Phoenix prompt playground, including running experiments over a dataset. Load before any playground tool call, including single-shot prompt rewrites.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[1038,1039,1040],{"name":936,"slug":937,"type":16},{"name":884,"slug":885,"type":16},{"name":1007,"slug":1008,"type":16},"2026-07-12T08:08:12.920792",{"slug":1043,"name":1043,"fn":1044,"description":1045,"org":1046,"tags":1047,"stars":974,"repoUrl":975,"updatedAt":1052},"span-coding","analyze and code Phoenix spans","Open-code Phoenix spans with PXI-owned notes, recover those notes for axial coding, and promote stable categories into structured annotations. Load this when analyzing spans to discover failure patterns before a taxonomy exists.\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[1048,1049,1050,1051],{"name":993,"slug":994,"type":16},{"name":884,"slug":885,"type":16},{"name":14,"slug":15,"type":16},{"name":973,"slug":35,"type":16},"2026-07-12T08:08:19.597239",{"slug":853,"name":853,"fn":854,"description":855,"org":1054,"tags":1055,"stars":20,"repoUrl":21,"updatedAt":867},{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[1056,1057,1058],{"name":859,"slug":860,"type":16},{"name":862,"slug":863,"type":16},{"name":865,"slug":866,"type":16},{"slug":869,"name":869,"fn":870,"description":871,"org":1060,"tags":1061,"stars":20,"repoUrl":21,"updatedAt":889},{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[1062,1063,1064,1065,1066],{"name":875,"slug":876,"type":16},{"name":878,"slug":879,"type":16},{"name":881,"slug":882,"type":16},{"name":884,"slug":885,"type":16},{"name":887,"slug":888,"type":16},{"slug":891,"name":891,"fn":892,"description":893,"org":1068,"tags":1069,"stars":20,"repoUrl":21,"updatedAt":901},{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[1070,1071,1072],{"name":897,"slug":898,"type":16},{"name":884,"slug":885,"type":16},{"name":14,"slug":15,"type":16},{"slug":903,"name":903,"fn":904,"description":905,"org":1074,"tags":1075,"stars":20,"repoUrl":21,"updatedAt":923},{"slug":8,"name":9,"logoUrl":10,"githubOrg":11},[1076,1077,1078,1079,1080],{"name":909,"slug":910,"type":16},{"name":912,"slug":913,"type":16},{"name":915,"slug":916,"type":16},{"name":918,"slug":919,"type":16},{"name":921,"slug":922,"type":16},23]