cx-ai-center

name	cx-ai-center
description	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. It covers both analyzing AI telemetry (GenAI spans) and managing AI Center config via the `cx ai-center` commands.
metadata	{"version":"0.1.0"}

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 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).

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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.

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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.

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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)

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. 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:

{
  "gpt-4o": {
    "inputPricePerMillionTokens": 2.5,
    "outputPricePerMillionTokens": 10,
    "cacheReadPricePerMillionTokens": 1.25,
    "cacheWritePricePerMillionTokens": 3.75
  }
}

An empty map {} clears all overrides (set replaces the whole set — it's team-wide, new data only).

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Common workflows

Inventory & guardrail gaps

# Which apps are NOT guarded?
cx ai-center applications list -o json | jq '[.[] | select(.guardrailsIntegrated==false)]'

Enable a policy on an app (write — confirm first!)

# 1. Describe to the user; 2. get approval; 3. then:
cx ai-center evaluations create --from-file eval.json --yes
# eval.json: { "application": "...", "subsystem": "...", "config": { "<type>": {...} }, "isEnabled": true }

Read the actual conversations (telemetry, not config)

Use cx spans with the query library in references/ai-center-queries.md — reading messages, cost, latency, errors, tool calls, and per-user analysis.

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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.

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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).