Phoenix CliCAUTION
AI Observability & Evaluation
Overview
AI Observability & Evaluation
d8c65ae926a8OBSERVED · 2026-10-20Host compatibility
What the documentation claims. We have not run a compatibility test.
| Host | Status | Notes |
|---|---|---|
| codex | mentioned | |
| cursor | mentioned |
What it tells the agent
The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.
---
name: phoenix-cli
description: Debug LLM applications using the Phoenix CLI (`px`, from @arizeai/phoenix-cli). Fetch traces, spans, and sessions, annotate them, analyze errors, measure how often a failure or pattern occurs across traces, inspect datasets, review experiments, query annotation configs, and use the GraphQL API. Use whenever the user works with a Phoenix instance from the terminal, or wants to measure or investigate something in Phoenix with the CLI.
license: Apache-2.0
compatibility: Requires Node.js (for npx) or global install of @arizeai/phoenix-cli. Optionally requires jq for JSON processing.
metadata:
author: arize-ai
version: "3.5.0"
---
# Phoenix CLI
## Invocation
```bash
px <resource> <action> # if installed globally
npx @arizeai/phoenix-cli <resource> <action> # no install required
```
The CLI uses singular resource commands with subcommands like `list` and `get`:
```bash
px trace list
px trace get <trace-id>
px trace annotate <trace-id>
px trace add-note <trace-id>
px trace delete <trace-identifier>
px trace-annotations delete
px span list
px span annotate <span-id>
px span add-note <span-id>
px span delete <span-identifier>
px span-annotations delete
px session list
px session get <session-id>
px session annotate <session-id>
px session add-note <session-id>
px session delete <session-id>
px session-annotations delete
px dataset list
px dataset get <name>
px dataset delete <dataset-identifier>
px experiment list
px experiment get <id>
px experiment delete <experiment-id>
px prompt list
px prompt get <prompt-identifier>
px prompt delete <prompt-identifier>
px project list
px project get <name>
px project delete <project-identifier>
px annotation-config list
px annotation-config get <identifier>
px annotation-config create
px annotation-config update <identifier>
px annotation-config delete <id>
px auth login
px auth logout
px auth status
px profile list
px profile show [name]
px profile create <name>
px profile use <name>
px profile edit <name>
px profile delete <name>
px api graphql <query>
px docs fetch
px setup
px self update
```
Every `delete` above is gated: it requires
`PHOENIX_CLI_DANGEROUSLY_ENABLE_DELETES=true` in the environment and prompts for
confirmation unless `-y`/`--yes` is passed (`px profile delete` is local-only and
takes `--yes` without the env gate). Without the env var the command exits
without deleting anything.
## Setup
```bash
export PHOENIX_ENDPOINT=http://localhost:6006
export PHOENIX_PROJECT=my-project
export PHOENIX_API_KEY=your-api-key # if auth is enabled
```
`PHOENIX_ENDPOINT` is the base URL for API access. It usually holds the same URL as `PHOENIX_COLLECTOR_ENDPOINT`; when only the collector variable is set, the CLI uses it for API access too.
For interactive local use, `px auth login` stores an OAuth session in the selected profile; the session acts with the permissions of the user who logged in. API keys take precedence over OAuth tokens when both are configured.
OAuth access tokens are refreshed automatically for REST, GraphQL, and PXI
requests, and rotated tokens are persisted to the selected profile.
Always use `--format raw --no-progress` when piping to `jq`.
### `px setup` — onboarding
`px setup` connects the app in the current directory to a Phoenix deployment
and writes `.env.phoenix` (mode 0600, gitignored). The interactive flow is for
humans — it prompts, launches coding agents, and polls for traces. **From an
agent, always pass `--no-input`:**
```bash
# Register only: connection + .env.phoenix, no source changes.
px setup --no-input --endpoint http://localhost:6006 --project my-app --format raw
```
Headless requires a clean git repo and, by default, stops after writing the
files — it will not touch source unless you ask. If auth is enabled, also set
`PHOENIX_API_KEY`. The project doesn't need to exist — Phoenix creates it on
first trace. Missing inputs exit `3` with exact remediation; cancel exits `2`.
To also instrument the app, name the lane — headless has no prompt to pick one
from, so `--instrument` requires `--agent`:
```bash
px setup --no-input --instrument --agent claude --yolo --format raw
```
`--yolo` matters: a background agent has no terminal to approve its edits on,
so without it the run stalls until trace verification times out. `--language
python` skips the agent's language detection. `--docs-mcp` connects the
Phoenix docs MCP server to the hand-off agent (`claude mcp add` for claude,
config-file merge for cursor/opencode; codex unsupported) and skips the
`.px/docs` download — the agent searches docs on demand instead; any failure
falls back to the download. `--no-docs-mcp` suppresses the interactive offer.
`--format raw` prints
`{"endpoint","project","files","instrumentation","tracesVerified","tracesUrl"}`
— check `tracesVerified`, which is set only when the API confirmed a trace
arriving, not when the agent claims it finished.
A run whose wait ran out with no trace exits `6`, not `0`: the configuration and
edits are real, but tracing is not confirmed working. Treat that as a failure to
report, not a success — and do not substitute the hand-off agent's own exit code
or summary for the verdict. Registering without `--instrument`, and a human
answering "verify later" at the timeout prompt, both exit `0`.
`tracesVerified` is `false` for a registration-only run too, so it alone can't
tell "nothing to verify" from "no trace arrived". Read `verification`
(`verified` / `notVerified` / `deferred`, absent when there was nothing to
verify) when you need the difference.
Re-runnable slices, so an already-registered repo skips the questions:
```bash
px setup instrument --agent claude # instrument + verify only
px setup skills # install the Phoenix coding-agent skills
```
### `px setup mcp` — register the remote MCP server
Wire the Phoenix remote MCP server (`<endpoint>/mcp`) into a coding agent so it
can query Phoenix data. The endpoinTrust audit
CAUTIONgrade B · trust 89/100 Install with care. The audit found things worth knowing before you trust its output.
| Layer | What it checks | Result |
|---|---|---|
| L0 | Provenance & inventory | WARN |
| L1 | Static analysis of the code | NA |
| L2 | Instruction surface (what it tells the agent) | PASS |
| L3 | Class-specific surface | PASS |
| L4 | Behavioural (sandbox) | SKIPPED |
What the source does
- Filesystem
- none-observed
- Network
- none-observed
- Shell
- none-observed
- Dependencies
- pinned
- Secrets in source
- none-found
Findings (5)
.claude/skills
.codex/skills
.cursor/skills/mintlify
.cursor/skills/vercel-react-best-practices
CLAUDE.md
Gates applied: no_behavioural_pass.
d8c65ae926a8full audit observations/trust-audit/skill/arize-ai__phoenix-cli.json · Report an issue / request a re-scanAudit history
Every audit this skill has had.
| Date | Source | Verdict | Grade | Score | Change |
|---|---|---|---|---|---|
| 2026-10-20 | d8c65ae926a8 | CAUTION | B | 89 | first audit |
Questions
What does the phoenix-cli — arize-ai/phoenix skill do?
AI Observability & Evaluation
Is phoenix-cli — arize-ai/phoenix safe to install?
With care. The audit graded it B (89/100) and found 5 things worth knowing before you trust this skill, listed below with the exact line each was found on.
What can phoenix-cli — arize-ai/phoenix access on my machine?
The audit observed no filesystem, network or shell use at all in its source.
Which assistants does phoenix-cli — arize-ai/phoenix work with?
Its documentation mentions codex and cursor. That is what the text claims, not a compatibility test we ran.
How current is this page?
The grade is for one exact copy of the source (d8c65ae926a8), read on 2026-10-20. The repository is watched, and a new audit runs when it changes — this is the first audit.
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