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).

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

~/.cx/config.toml

. To skip the prompt in scripts, pass

--yes

IMPORTANT: NEVER pass
--yes
without explicit user approval. Before executing any write:

Describe the exact operation to the user (what will be created/modified/deleted/linked).
Wait for the user to confirm.
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.

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

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:

json

{
  "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).

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

bash

# 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!)

bash

# 1. Describe to the user; 2. get approval; 3. then:
cx ai-center evaluations create --from-file eval.json --yes
# eval.json: { "application": "...", "subsystem": "...", "target": "PROMPT", "config": { "<type>": {...} }, "isEnabled": true }
# `target` is REQUIRED and must be UPPERCASE — "PROMPT" or "RESPONSE" (the API rejects lowercase / a missing target).

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.

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
```
).

cx-ai-center

NPX Install

Tags

SKILL.md Content