mcpField
C
cx-ai-center

cx-ai-center

github.com/coralogixCloud & DevOps2152.4k installsUpdated today
Repository

About cx-ai-center

cx-ai-center is a skill for managing and analyzing Coralogix AI applications, covering configuration policies and GenAI telemetry. It distinguishes application configuration from span queries and requires confirmation for write operations.

Key features

  1. 01Inspect AI apps and guardrail status
  2. 02Manage evaluations and app links
  3. 03Analyze GenAI span telemetry
  4. 04View evaluation coverage and model pricing
  5. 05Require confirmation for writes

Use cases

  1. 01Find apps without integrated guardrails
  2. 02Check whether policies are linked to apps
  3. 03Analyze conversations, cost, latency, and errors
  4. 04Review evaluation coverage or model prices

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/coralogix/cx-cli --skill cx-ai-center

After installing, type/cx-ai-centerin Claude Code to confirm it loaded.

Bundled files

References and scripts installed along with SKILL.md.

references/
ai-center-queries.md
dataprime-reference.md
spans-querying.md

Details

From the project README

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 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.


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)
CommandPurpose
cx ai-center applications listList 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)
CommandPurpose
cx ai-center evaluations listAll 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.jsonCreate/enable an evaluation (write)
cx ai-center evaluations update <evaluation-id> --from-file patch.jsonPartial update (write)
cx ai-center evaluations delete <evaluation-id>Remove an evaluation from its app (write)
Custom evaluations (policies) & application links
CommandPurpose
cx ai-center custom-evaluations listAll 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.jsonCreate a custom policy (write)
cx ai-center custom-evaluations update <id> --from-file patch.jsonPartial 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
CommandPurpose
cx ai-center coverageMap of each evaluation type → number of apps using it (coverage / gap analysis)
cx ai-center model-pricing getTeam's custom per-model pricing overrides
cx ai-center model-pricing set --from-file prices.jsonSet 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:

{
  "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
# 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": "...", "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).

Comments

Markdown supported