Use this skill for any question or action about the user's AI/GenAI applications or agents — their behavior, prompts/responses, quality, hallucinations, guardrails, security, cost/tokens, errors, evaluations/policies, model pricing, or configuration — including comparing or tracking agents over time

AI Center Skill This is the tool for anything about AI/GenAI applications — both questions about their behavior (prompts/responses, quality, hallucinations, guardrails, security, cost/tokens, errors, latency — everything AI apps expose through their GenAI spans/tags) and actions to manage them (applications, evaluations/policies, policy↔app links, model pricing). If a request touches an AI application or its GenAI telemetry, use this skill. Coralogix AI Center observes, evaluates, and guards GenAI/LLM applications. This skill answers questions about AI apps from two sources: Configuration (this skill's cx ai center commands): the AI application inventory, configured evaluations/policies, coverage, custom evaluations, and model pricing — none of which live in span telemetry. Telemetry (GenAI spans): what users asked, how the model answered, cost, tokens, latency, errors, tool calls, and eval/guardrail verdicts — queried with cx spans '<DataPrime ' . See [references/ai center queries.md](references/ai center queries.md) for the full, runnable query library, span schema, and playbooks. Match the source to the question: "which apps lack guardrails" → config ( cx ai center applications list ); "what are users asking my chatbot" → telemetry ( cx spans '…' , reading the conversation from the GenAI spans). Some questions need both — e.g. "is my chatbot's PII policy actually catching PII?" joins config (is the policy enabled) with telemetry (the PII verdicts + the messages). Destructive Operation Safety All write operations ( create , update , delete , add , remove , set ) require interactive confirmation. ai center is a risky command, so writes are also gated by allow risky commands in ~/.cx/config.toml . To skip the prompt in scripts, pass yes . IMPORTANT: NEVER pass yes without explicit user approval. Before executing any write: 1. Describe the exact operation to the user (what will be created/modified/deleted/linked). 2. Wait for the user to confirm. 3. Only then execute with yes . Read operations ( list , get , coverage , list for application , model pricing get ) do not require confirmation and can be run freely. Read Only Mode Use read only (or CX READ ONLY=1 ) to block every write at the CLI level — safe for exploration. Agent Mode When running inside an AI agent (Claude Code, Cursor, Codex, …), cx detects it and — instead of showing a confirmation prompt that would hang forever (no human is there to type y/n) — stops immediately with an error telling you to get the user's approval, then re run with yes . No delete commands (by design) The CLI intentionally exposes no delete for custom evaluation policies, AI applications, or model pricing — even though the AI v3 API has those delete endpoints, cx ai center does not surface them. Custom evaluation policy: can't be deleted; to take it off an app, detach with custom evaluations remove (the policy object survives and can be re attached). Model pricing: no delete command. It's team wide (not per app), so to change or clear it, run model pricing set with a new map (an empty map {} clears all overrides) — set replaces the whole set. Golden rule For content questions (quality, hallucination, sentiment, topics) read the actual conversation and cite the traceID — don't rely on verdict tags alone. The transcript lives in one of two conventions ( gen ai.input.messages / output.messages , or the older indexed gen ai.prompt.<n / completion.<n tags); read it with the Reading conversations (content questions) queries in the library, which handle both and exclude the system prompt and tool traffic. Full guidance: [references/ai center queries.md](references/ai center queries.md). CLI Commands Show names to the user; use UUIDs only internally. When presenting results, refer to apps and evaluations by their human names (application/subsystem, evaluation name), not raw UUIDs. The UUID is only needed to call a by id or write command — resolve it yourself from the matching list command (never guess or make the user paste a UUID). Applications (inventory + guarded status) Command Purpose cx ai center applications list List AI apps incl. guardrailsIntegrated (guarded) status cx ai center applications list evaluation type <TYPE Filter to apps using an eval type (repeatable) cx ai center applications list page size <N page offset <N Paginate cx ai center applications get <application id One application by UUID Evaluations (configured policies on apps) Command Purpose cx ai center evaluations list All configured evaluations cx ai center evaluations list application <app subsystem <sub Scope to one app (the pair) cx ai center evaluations list evaluation type <TYPE Filter by type — <TYPE is the API enum (e.g. PII , TOXICITY , PROMPT INJECTION ; the keys from coverage ), not the lowercase form cx ai center evaluations get <evaluation id One evaluation by UUID cx ai center evaluations create from file eval.json Create/enable an evaluation (write) cx ai center evaluations update <evaluation id from file patch.json Partial update (write) cx ai center evaluations delete <evaluation id Remove an evaluation from its app (write) Custom evaluations (policies) & application links Command Purpose cx ai center custom evaluations list All custom evaluation policies cx ai center custom evaluations list for application <application id Policies linked to one app cx ai center custom evaluations create from file policy.json Create a custom policy (write) cx ai center custom evaluations update <id from file patch.json Partial update (write) cx ai center custom evaluations add <evaluation id <application id Attach a policy to an app (write) cx ai center custom evaluations remove <evaluation id <application id Detach (reversible) (write) By id is prebuilt only. evaluations get <id fetches a prebuilt/configured evaluation. Custom policies have no get by id — find one via custom evaluations list / list for application and match by id /name. Coverage & model pricing Command Purpose cx ai center coverage Map of each evaluation type → number of apps using it (coverage / gap analysis) cx ai center model pricing get Team's custom per model pricing overrides cx ai center model pricing set from file prices.json Set team pricing (team wide, new data only) (write) The from file bodies for evaluations and custom evaluations match the AI v3 API shape verbatim; use to read JSON from stdin. For evaluations create , target is required and must be uppercase ( PROMPT or RESPONSE ); for custom evaluations create , name , instructions , and policyType are required. Exception: model pricing set takes just the raw model→price map — cx wraps it as {"prices": …} for you, so do not include the outer prices envelope. Each model maps to a price object; all four fields are optional doubles (USD per one million tokens), omit the ones that don't apply: An empty map {} clears all overrides (set replaces the whole set — it's team wide, new data only). model pricing get returns the wrapper { "pricing": { "id", "companyId", "prices": { … } } } — the per model overrides live under prices (empty when none are set). Common workflows Inventory & guardrail gaps Enable a policy on an app (write — confirm first!) Read the actual conversations (telemetry, not config) Use cx spans with the query library in [references/ai center queries.md](references/ai center queries.md) — reading messages, cost, latency, errors, tool calls, and per user analysis. Key principles Config vs. telemetry: inventory / evaluations / policies / coverage / pricing → cx ai center ; content / cost / latency / errors / verdicts → GenAI spans via cx spans . Don't answer one from the other. Confirm before writes. Describe the operation, get approval, then run with yes . Related Skills cx telemetry querying — general logs/spans/metrics/DataPrime querying (the engine behind the cx spans queries used here). cx olly — the conversational AI assistant ( cx olly ask ).

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