Agentsop HTTP Tool Wrapping
agentsope/SkillAlchemy
Decision protocol for wrapping a REST / GraphQL / RPC API as a tool an LLM agent can call.
Debug LLM applications using the Phoenix CLI. An agent skill from Arize-ai/phoenix.
$ npx skills add Arize-ai/phoenix --skill phoenix-cli -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install Arize-ai/phoenix phoenix-cli --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/Arize-ai/phoenix.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/phoenix-cli .claude/skills/phoenix-cli && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "phoenix-cli" agent skill from https://github.com/Arize-ai/phoenix/tree/main/.agents/skills/phoenix-cli into .claude/skills/phoenix-cli/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "phoenix-cli", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/Arize-ai/phoenix/tree/main/.agents/skills/phoenix-cliType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add Arize-ai/phoenix --skill phoenix-cli -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install Arize-ai/phoenix phoenix-cli --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Arize-ai/phoenix.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.agents/skills/phoenix-cli .agents/skills/phoenix-cli && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "phoenix-cli" agent skill from https://github.com/Arize-ai/phoenix/tree/main/.agents/skills/phoenix-cli into .agents/skills/phoenix-cli/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "phoenix-cli", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add Arize-ai/phoenix --skill phoenix-cli -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install Arize-ai/phoenix phoenix-cli --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Arize-ai/phoenix.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.agents/skills/phoenix-cli .cursor/skills/phoenix-cli && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "phoenix-cli" agent skill from https://github.com/Arize-ai/phoenix/tree/main/.agents/skills/phoenix-cli into .cursor/skills/phoenix-cli/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "phoenix-cli", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/Arize-ai/phoenix.git --path .agents/skills/phoenix-cli--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add Arize-ai/phoenix --skill phoenix-cli -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install Arize-ai/phoenix phoenix-cli --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Arize-ai/phoenix.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.agents/skills/phoenix-cli .gemini/skills/phoenix-cli && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "phoenix-cli" agent skill from https://github.com/Arize-ai/phoenix/tree/main/.agents/skills/phoenix-cli into .gemini/skills/phoenix-cli/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "phoenix-cli", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install Arize-ai/phoenix phoenix-cliInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add Arize-ai/phoenix --skill phoenix-cli -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/Arize-ai/phoenix.git skills-src && mkdir -p .github/skills && cp -r skills-src/.agents/skills/phoenix-cli .github/skills/phoenix-cli && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "phoenix-cli" agent skill from https://github.com/Arize-ai/phoenix/tree/main/.agents/skills/phoenix-cli into .github/skills/phoenix-cli/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "phoenix-cli", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add Arize-ai/phoenix --skill phoenix-cli -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install Arize-ai/phoenix phoenix-cli --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/Arize-ai/phoenix.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.agents/skills/phoenix-cli .opencode/skills/phoenix-cli && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "phoenix-cli" agent skill from https://github.com/Arize-ai/phoenix/tree/main/.agents/skills/phoenix-cli into .opencode/skills/phoenix-cli/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "phoenix-cli", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
phoenix-cliDebug LLM applications using the Phoenix CLI. An agent skill from Arize-ai/phoenix.
Phoenix CLI is an agent skill from Arize-ai/phoenix. Debug LLM applications using the Phoenix CLI. Fetch traces, spans, and sessions, annotate them, analyze errors, inspect datasets, review experiments, query annotation configs, and use the GraphQL API. Use whenever the user works with a Phoenix instance from the terminal.
Its SKILL.md is about 6.8k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including reference files (for example `references/filter-expressions.md`). Compatibility notes: Requires Node.js (for npx) or global install of @arizeai/phoenix-cli. Optionally requires jq for JSON processing.
It sits in AI & LLM Engineering, covering LLM observability and GraphQL. It works with GraphQL and Model Context Protocol. The repository describes itself as: AI Observability & Evaluation. The licence is Apache-2.0.
Read from SKILL.md and the folder at commit 856100b. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Shell commands in SKILL.md call:
jqnpxcurlclaudeFrom the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md. Its commands use npx and curl, which can reach the network depending on how they are called.
From URLs in SKILL.md, links to its own repository left out.
Names these keys or tokens, usually read from environment variables:
PHOENIX_API_KEYFrom names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Requires Node.js (for npx) or global install of @arizeai/phoenix-cli. Optionally requires jq for JSON processing.
From compatibility in the SKILL.md frontmatter.
Phoenix CLI loads about 6.8k tokens when it runs, and up to ~11k if it reads all its reference files. Until then it costs about 71 tokens; SKILL.md has 1,375 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check noted patterns worth knowing about, such as sudo or a known installer.
and writes `.env.phoenix` (mode 0600, gitignored). The interactive flow is for# Register only: connection + .env.phoenix, no source changes.s > env vars > active profile > nearest `.env.phoenix` file > built-in defaults.The CLI also discovers the nearest `.env.phoenix` file at or above the current working directory (the same file `px setuAutomated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from Arize-ai/phoenix at commit 856100b, republished under its Apache-2.0 licence (© Arize-ai). 1,375 words, ~6,824 tokens.
.claude/skills/phoenix-cli/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.px <resource> <action> # if installed globally
npx @arizeai/phoenix-cli <resource> <action> # no install requiredThe CLI uses singular resource commands with subcommands like list and get:
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 updateEvery 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.
export PHOENIX_ENDPOINT=http://localhost:6006
export PHOENIX_PROJECT=my-project
export PHOENIX_API_KEY=your-api-key # if auth is enabledPHOENIX_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 — onboardingpx 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:
# Register only: connection + .env.phoenix, no source changes.
px setup --no-input --endpoint http://localhost:6006 --project my-app --format rawHeadless 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:
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:
px setup instrument --agent claude # instrument + verify only
px setup skills # install the Phoenix coding-agent skillspx setup mcp — register the remote MCP serverWire the Phoenix remote MCP server (<endpoint>/mcp) into a coding agent so it
can query Phoenix data. The endpoint is inferred from --endpoint, the active
profile, or PHOENIX_ENDPOINT. Bare command prompts for scope (global default) then
agent; --agent skips both prompts.
px setup mcp --agent codex --no-input --format raw
px setup mcp --agent claude --local # write this repo's .mcp.jsonAgents: claude, codex, gemini, cursor, opencode, vscode. Scope is
--global (default) or --local (repo; Codex is global-only). Auth is OAuth by
default (URL-only config, browser login on first use); pass --header "Name: value" (repeatable) for an API-key bearer fallback — for Codex a
Authorization: Bearer ${VAR} header becomes bearer_token_env_var. --format raw prints {"endpoint","url","serverName","agent","scope","auth","file?"}.
px auth login # browser-based OAuth login
px auth login --no-browser # print URL for SSH/headless use
px auth logout # clear OAuth tokens; leaves API keys
px auth status # check connection and authentication
px auth status --endpoint http://other:6006 # check a specific endpoint
px auth status --profile staging # check a named profile's connection
px auth status --format raw # machine-readable credential sourceauth status reports the credential source (flag, env, profile-key, oauth, or none). OAuth status includes the token expiry.
When the stored credential source is oauth and the authenticated probe fails,
auth status retries once without credentials and reports anonymous access only
if the server explicitly says access is anonymous. This keeps a stale or expired
profile token from being reported as an auth failure against a deployment that
has since switched from OAuth to anonymous access.
Named profiles let you switch between multiple Phoenix instances (local, staging, cloud) without juggling environment variables. Profiles are stored in ~/.px/settings.json (or $XDG_CONFIG_HOME/px/settings.json).
Configuration priority (highest to lowest): CLI flags > env vars > active profile > nearest .env.phoenix file > built-in defaults.
The CLI also discovers the nearest .env.phoenix file at or above the current working directory (the same file px setup writes). Credentials are resolved as one group, so a process API key is never combined with file-provided headers. Set PHOENIX_DISCOVER_CONFIG=false to disable discovery.
px profile list # list all profiles (shows active profile)
px profile show # show the active profile's settings
px profile show staging # show a named profile's settings
px profile create prod --endpoint https://app.phoenix.arize.com --api-key <key> --activate
px profile create local --endpoint http://localhost:6006 --project my-app
px profile use prod # switch the active profile
px profile edit prod # open profile JSON in $EDITOR (validates on save)
px profile delete prod --yes # delete a profile (--yes skips confirmation)Use --profile <name> on any command to target a specific profile without changing the active one:
px trace list --profile staging --limit 10 --format raw --no-progress | jq .
px auth status --profile prodpx profile create options: --endpoint <url>, --project <name>, --api-key <key>, --header <key=value> (repeatable), --activate.
px project list # list all projects (table view)
px project list --format raw --no-progress | jq '.[].name' # project names as JSON
px project list --name-contains prod # filter by name substring (case-insensitive)
px project get my-project --format raw --no-progress # single record by exact name
px project get my-project --format raw --no-progress | jq -r '.id' # extract project idproject list accepts --limit <n> (projects fetched per page) and
--name-contains <filter>, which filters server-side on a case-insensitive name
substring. Use it instead of piping list through grep when you only know part
of a project's name.
project get exits with ExitCode.FAILURE (1) on a name miss and writes a StructuredError {error, code: "FAILURE", hint} to stderr in --format json|raw.
px trace list --limit 20 --format raw --no-progress | jq .
px trace list --last-n-minutes 60 --limit 20 --format raw --no-progress | jq '.[] | select(.status == "ERROR")'
px trace list --since 2025-01-15T00:00:00Z --limit 50 --format raw --no-progress | jq .
px trace list --since 2025-01-15T00:00:00Z --until 2025-01-16T00:00:00Z --limit 50 --format raw --no-progress | jq . # time range (until is exclusive)
px trace list --format raw --no-progress | jq 'sort_by(-.duration) | .[0:5]'
px trace list --include-notes --format raw --no-progress | jq '.[].notes'
px trace get <trace-id> --format raw | jq .
px trace get <trace-id> --format raw | jq '.spans[] | select(.status_code != "OK")'
px trace get <trace-id> --include-notes --format raw | jq '.notes'
px trace annotate <trace-id> --name reviewer --label pass
px trace annotate <trace-id> --name reviewer --score 0.9 --format raw --no-progress
px trace annotate <trace-id> --name reviewer --label pass --identifier "<coding-annotation-id>" # tag with a coding annotation identifier
px trace add-note <trace-id> --text "needs follow-up"
px trace add-note <trace-id> --text "needs follow-up" --identifier "<coding-annotation-id>" # tag + upsert on identifier
px trace-annotations delete --identifier "<coding-annotation-id>" --all -y # nuke every annotation tied to this coding annotation identifierpx <entity>-annotations delete requires --all or both --start-time and --end-time and emits {deleted: true, target, filter} on success.
Trace
traceId, status ("OK"|"ERROR"), duration (ms), startTime, endTime
annotations[] (with --include-annotations, excludes note)
name, result { score, label, explanation }
notes[] (with --include-notes)
name="note", result { explanation }
rootSpan — top-level span (parent_id: null)
spans[]
name, span_kind ("LLM"|"CHAIN"|"TOOL"|"RETRIEVER"|"EMBEDDING"|"AGENT"|"RERANKER"|"GUARDRAIL"|"EVALUATOR"|"DECISION"|"UNKNOWN")
status_code ("OK"|"ERROR"|"UNSET"), parent_id, context.span_id
notes[] (with --include-notes)
name="note", result { explanation }
attributes
input.value, output.value — raw input/output
llm.model_name, llm.provider
llm.token_count.prompt/completion/total
llm.token_count.prompt_details.cache_read
llm.token_count.completion_details.reasoning
llm.input_messages.{N}.message.role/content
llm.output_messages.{N}.message.role/content
llm.invocation_parameters — JSON string (temperature, etc.)
exception.message — set if span erroredpx span list --limit 20 # recent spans (table view)
px span list --last-n-minutes 60 --limit 50 # spans from last hour
px span list --since 2025-01-15T00:00:00Z --limit 50 # spans since a timestamp
px span list --since 2025-01-15T00:00:00Z --until 2025-01-16T00:00:00Z --limit 50 # time range (until is exclusive)
px span list --span-kind LLM --limit 10 # only LLM spans
px span list --status-code ERROR --limit 20 # only errored spans
px span list --name chat_completion --limit 10 # filter by span name
px span list --trace-id <id> --format raw --no-progress | jq . # all spans for a trace
px span list --span-id <id> <id> --format raw --no-progress | jq . # fetch specific spans by ID (server >= 19.6.0)
px span list --parent-id null --limit 10 # only root spans
px span list --parent-id <span-id> --limit 10 # only children of a span
px span list --include-annotations --limit 10 # include annotation scores
px span list --include-notes --limit 10 # include span notes
px span list --attribute llm.model_name:gpt-4 --limit 10 # filter by string attribute
px span list --attribute llm.token_count.total:500 --limit 10 # filter by numeric attribute
px span list --attribute 'user.id:"12345"' --limit 10 # force string match for numeric-looking value
px span list --attribute session.id:sess:abc:123 --limit 20 # colon in value OK (split on first colon only)
px span list --attribute llm.model_name:gpt-4 --attribute session.id:abc --limit 10 # AND multiple filters
px span list output.json --limit 100 # save to JSON file
px span list --format raw --no-progress | jq '.[] | select(.status_code == "ERROR")'
px span annotate <span-id> --name reviewer --label pass
px span annotate <span-id> --name checker --score 1 --annotator-kind CODE
px span annotate <span-id> --name reviewer --label pass --identifier "<coding-annotation-id>" # tag with a coding annotation identifier
px span add-note <span-id> --text "verified by agent"
px span add-note <span-id> --text "verified by agent" --identifier "<coding-annotation-id>" # tag + upsert on identifier
px span-annotations delete --identifier "<coding-annotation-id>" --all -y # nuke every annotation tied to this coding annotation identifierspan list orders by ingestion (newest first), not start_time; they diverge for late-arriving spans (backfills, replays). To sort by start_time (server >= 20.16.0), call REST and keep sort/order fixed across next_cursor pages:
curl -s -H "Authorization: Bearer $PHOENIX_API_KEY" \
"$PHOENIX_ENDPOINT/v1/projects/my-project/spans?sort=start_time&order=desc&limit=20"Span
name, span_kind ("LLM"|"CHAIN"|"TOOL"|"RETRIEVER"|"EMBEDDING"|"AGENT"|"RERANKER"|"GUARDRAIL"|"EVALUATOR"|"DECISION"|"UNKNOWN")
status_code ("OK"|"ERROR"|"UNSET"), status_message
context.span_id, context.trace_id, parent_id
start_time, end_time
attributes
input.value, output.value — raw input/output
llm.model_name, llm.provider
llm.token_count.prompt/completion/total
llm.input_messages.{N}.message.role/content
llm.output_messages.{N}.message.role/content
llm.invocation_parameters — JSON string (temperature, etc.)
exception.message — set if span errored
annotations[] (with --include-annotations, excludes note)
name, result { score, label, explanation }
notes[] (with --include-notes)
name="note", result { explanation }px session list --limit 10 --format raw --no-progress | jq .
px session list --order asc --format raw --no-progress | jq '.[].session_id'
px session list --include-annotations --include-notes --format raw --no-progress | jq '.[].notes'
px session get <session-id> --format raw | jq .
px session get <session-id> --include-annotations --format raw | jq '.session.annotations'
px session get <session-id> --include-notes --format raw | jq '.session.notes'
px session annotate <session-id> --name reviewer --label pass
px session annotate <session-id> --name reviewer --score 0.9 --format raw --no-progress
px session annotate <session-id> --name reviewer --label pass --identifier "<coding-annotation-id>" # tag with a coding annotation identifier
px session add-note <session-id> --text "verified by agent"
px session add-note <session-id> --text "verified by agent" --identifier "<coding-annotation-id>" # tag + upsert on identifier
px session-annotations delete --identifier "<coding-annotation-id>" --all -y # nuke every annotation tied to this coding annotation identifier
px session delete <session-id> -y # requires PHOENIX_CLI_DANGEROUSLY_ENABLE_DELETES=truesession list has no filter flag. To select sessions by shape — error counts,
token totals, tool use, annotation labels — use the session filter expression
language through GraphQL (see Session filter expressions).
SessionData
id, session_id, project_id
start_time, end_time
token_count_prompt, token_count_completion, token_count_total — cumulative across all LLM spans in the session (int, default 0)
annotations[] (with --include-annotations, excludes note)
name, result { score, label, explanation }
notes[] (with --include-notes)
name="note", result { explanation }
traces[]
id, trace_id, start_time, end_timepx dataset list --format raw --no-progress | jq '.[].name'
px dataset get <name> --format raw | jq '.examples[] | {input, output: .expected_output}'
px dataset get <name> --split train --format raw | jq . # filter by split
px dataset get <name> --version <version-id> --format raw | jq .
px experiment list --dataset <name> --format raw --no-progress | jq '.[] | {id, name, failed_run_count}'
px experiment get <id> --format raw --no-progress | jq '.[] | select(.error != null) | {input, error}'
px prompt list --format raw --no-progress | jq '.[].name'
px prompt get <name> --format text --no-progress # plain text, ideal for piping to AIFull CRUD: list, get, create, update, delete. Types are CATEGORICAL (labels + optional scores), CONTINUOUS (numeric range), FREEFORM (free text).
px annotation-config list # all configs (table view)
px annotation-config list --format raw --no-progress | jq -r '.[].name' # config names as JSON
px annotation-config get response-quality --format raw --no-progress # one config by name or ID
# create — categorical (scored labels), continuous (numeric range), or freeform (free text)
px annotation-config create --type CATEGORICAL --name response-quality --value good=1 --value bad=0
px annotation-config create --type CONTINUOUS --name confidence --lower-bound 0 --upper-bound 1
px annotation-config create --type FREEFORM --name reviewer-notes --description 'Free-form reviewer feedback'
# update by name or ID — only the fields you pass change; type is immutable
px annotation-config update response-quality --name answer-quality --optimization-direction MAXIMIZE
px annotation-config update response-quality --value good=1 --value acceptable=0.5 --value bad=0
px annotation-config update response-quality --description "Updated" --format raw --no-progress | jq -r '.id'
# delete by ID — requires PHOENIX_CLI_DANGEROUSLY_ENABLE_DELETES=true; --yes skips the prompt
px annotation-config delete QW5ub3RhdGlvbkNvbmZpZzoxMjM= --yesCategorical values are specified the same way in create and update: repeatable --value label[=score] (score optional), or a single --values '<json>' payload — mutually exclusive. update fetches the existing config, merges your flags, and writes the full body back via PUT /v1/annotation_configs/{id}; it requires at least one field flag. Other type-specific flags: --lower-bound/--upper-bound (CONTINUOUS/FREEFORM), --threshold (FREEFORM). Invalid input (bad flags, type mismatches, malformed values) exits 3 (INVALID_ARGUMENT) with a {error, code, hint?} JSON envelope on stderr in raw/json mode. get/create/update output the config object (single object in raw/json, not an array).
For ad-hoc queries not covered by the commands above. Output is {"data": {...}}.
px api graphql '{ projectCount datasetCount promptCount evaluatorCount }'
px api graphql '{ projects { edges { node { name traceCount tokenCountTotal } } } }' | jq '.data.projects.edges[].node'
px api graphql '{ datasets { edges { node { name exampleCount experimentCount } } } }' | jq '.data.datasets.edges[].node'
px api graphql '{ evaluators { edges { node { name kind } } } }' | jq '.data.evaluators.edges[].node'
# evaluator kind values: "LLM" | "CODE" | "BUILTIN"
# CODE = server-side code evaluator running in a sandbox; BUILTIN = pre-built server evaluator
# Introspect any type
px api graphql '{ __type(name: "Project") { fields { name type { name } } } }' | jq '.data.__type.fields[]'Key root fields: projects, getProjectByName(name:), datasets, prompts, evaluators, projectCount, datasetCount, promptCount, evaluatorCount, viewer.
getProjectByName(name:) targets one project; projects(first: 1) picks an
arbitrary one. There is no traces connection: to list traces, query spans
with filterCondition: "parent_span is None", which keeps root spans, as the
UI's traces table does. See Filter expressions below.
spans, sessions, and the project aggregates take filter conditions: Python
boolean expressions compiled server-side. There are three languages, and the
argument picks the language. Read
references/filter-expressions.md before
writing a condition; it has the full vocabulary, operators, and compiled
examples for each.
| Argument | Matches | Names come from |
|---|---|---|
filterCondition | individual spans | the exhaustive table in the reference |
traceFilterCondition | whole traces | traceFilterVocabulary |
sessionFilterCondition | sessions | sessionFilterVocabulary |
Root spans. There is no traces connection and no root-span argument.
filterCondition: "parent_span is None" keeps root spans, including orphans
whose parent was never received, and is what the UI's traces table runs;
parent_id is None keeps only spans with no parent id. A root span is usually
one per trace, and either clause composes with the rest of the filter:
px api graphql '{
getProjectByName(name: "default") { spans(
first: 20
filterCondition: "parent_id is None and status_code == \"ERROR\""
sort: { col: startTime, dir: desc }
) { edges { node { spanId name latencyMs } } } }
}' | jq '.data.getProjectByName.spans.edges[].node'Annotations. The accessor picks the level, and the wrong level matches nothing:
| Accessor | Matches annotations on | Written by |
|---|---|---|
annotations["name"] | the span itself | px span annotate, px span add-note |
trace_annotations["name"] | the span's parent trace | px trace annotate, px trace add-note |
session_annotations["name"] | the session (session filter only) | px session annotate, px session add-note |
px api graphql '{
getProjectByName(name: "default") { spans(
first: 20
filterCondition: "parent_id is None and trace_annotations[\"quality\"].label == \"poor\""
) { edges { node { spanId name } } } }
}' | jq '.data.getProjectByName.spans.edges[].node'Traces. traceFilterCondition keeps the spans of matching traces and
composes with filterCondition:
px api graphql '{
getProjectByName(name: "default") { spans(
first: 20
filterCondition: "parent_id is None"
traceFilterCondition: "error_count > 0 and latency_ms > 1000"
) { edges { node { spanId name latencyMs } } } }
}' | jq '.data.getProjectByName.spans.edges[].node'Sessions. px session list has no filter flag, so selecting sessions by
shape goes through GraphQL:
px api graphql '{
projects(first: 1) { edges { node { sessions(
first: 10
sessionFilterCondition: "num_traces > 5 and any(span.status_code == \"ERROR\" for span in spans)"
) { edges { node { sessionId numTraces numTracesWithError } } } } } }
}' | jq '.data.projects.edges[0].node.sessions.edges[].node'Discover names and validate. The vocabularies are generated from the compiler's own bindings, so they always match what compiles:
px api graphql '{ projects(first: 1) { edges { node { traceFilterVocabulary {
name type category description iterableName } } } } }' \
| jq '.data.projects.edges[0].node.traceFilterVocabulary[] | {name, type, category}'
px api graphql '{ projects(first: 1) { edges { node {
validateSpanFilterCondition(condition: "parent_id is None") { isValid errorMessage }
validateTraceFilterCondition(condition: "error_count > 0") { isValid errorMessage }
validateSessionFilterCondition(condition: "num_traces > 5") { isValid errorMessage }
} } } }'On fields that accept both levels (e.g. Project.recordCount),
sessionFilterCondition and filterCondition are mutually exclusive.
Download Phoenix documentation markdown for local use by coding agents.
px docs fetch # fetch default workflow docs to .px/docs
px docs fetch --workflow tracing # fetch only tracing docs
px docs fetch --workflow tracing --workflow evaluation
px docs fetch --dry-run # preview what would be downloaded
px docs fetch --refresh # clear .px/docs and re-download
px docs fetch --output-dir ./my-docs # custom output directoryKey options: --workflow (repeatable, values: tracing, evaluation, datasets, prompts, integrations, sdk, self-hosting, all), --dry-run, --refresh, --output-dir (default .px/docs), --workers (default 10).
© Arize-ai, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 1 other file (references) in .agents/skills/phoenix-cli of Arize-ai/phoenix.
Open the folder on GitHubat commit 856100b
Phoenix CLI next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Phoenix CLI this skillArize-ai/phoenix | 12k | — | ~6.8k | Automated safety check: Notes | Apache-2.0 | |
| Agentsop HTTP Tool Wrappingagentsope/SkillAlchemy | 459 | — | ~5.9k | Automated safety check: Pass | MIT | |
| Phoenix CLIgithub/awesome-copilot | 40k | 2 repos | ~4k | Automated safety check: Pass | Apache-2.0 | |
| Spider Kingaoyunyang/spider-king-skill | 507 | — | ~7.3k | Automated safety check: Pass | MIT | |
| Build Error AdapterArcadeAI/arcade-mcp | 1k | — | ~2k | Automated safety check: Pass | MIT | |
| Cuga GitHub Issuescuga-project/cuga-agent | 895 | — | ~1.2k | Automated safety check: Pass | Custom licence |
agentsope/SkillAlchemy
Decision protocol for wrapping a REST / GraphQL / RPC API as a tool an LLM agent can call.
github/awesome-copilot
Debug LLM applications using the Phoenix CLI. An agent skill from github/awesome-copilot.
aoyunyang/spider-king-skill
Pure-web protocol reverse skill: turn hostile browser clients into browser-free Python collectors.
ArcadeAI/arcade-mcp
Build new Arcade error adapters from scratch using public Arcade TDK patterns.
cuga-project/cuga-agent
Create GitHub issues for cuga-agent (bugs, features, epics, designs, and related work) against origin using gh, with epic → feature → issue hierarchy and GraphQL sub-issue linking.
apollographql/apollo-mcp-server
Syncs MCP Apps documentation with the @apollo/client-ai-apps changelog.
Arize-ai/phoenix
A skill your agent uses when working with Harbor's harbor exec CLI workflow: compiling files, directories, or globs into Harbor tasks; running map jobs; configuring artifacts and existence-only…
Arize-ai/phoenix
Build and maintain documentation sites with Mintlify. An agent skill from Arize-ai/phoenix.
Arize-ai/phoenix
Frontend development guidelines for the Phoenix AI observability platform.
Arize-ai/phoenix
Write efficient GraphQL queries against the Phoenix API. An agent skill from Arize-ai/phoenix.
Arize-ai/phoenix
Backend development guide for the Phoenix AI observability platform (Strawberry GraphQL, SQLAlchemy async, FastAPI).
Arize-ai/phoenix
Conventions for creating, modifying, and reviewing production-faithful Storybook stories in the Phoenix frontend (js/app/stories, js/app/.storybook).
Works with
Categories
Debug LLM applications using the Phoenix CLI. An agent skill from Arize-ai/phoenix. Phoenix CLI is an agent skill from Arize-ai/phoenix. Debug LLM applications using the Phoenix CLI.
Phoenix CLI fits situations like: the user works with a Phoenix instance from the terminal; tasks that involve LLM observability; tasks that involve GraphQL.
Run `npx skills add Arize-ai/phoenix --skill phoenix-cli -a claude-code`. Or copy the skill folder (.agents/skills/phoenix-cli in Arize-ai/phoenix) into .claude/skills/phoenix-cli in your project. Claude Code loads it when a task matches its description.
Run `npx skills add Arize-ai/phoenix --skill phoenix-cli -a codex`. Or copy the skill folder (.agents/skills/phoenix-cli in Arize-ai/phoenix) into .agents/skills/phoenix-cli in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add Arize-ai/phoenix --skill phoenix-cli -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/phoenix-cli, .gemini/skills/phoenix-cli, .github/skills/phoenix-cli and .opencode/skills/phoenix-cli in your project.
Going by SKILL.md and its folder, Phoenix CLI needs the command-line tools its instructions call (jq, npx, curl and claude) and credentials named PHOENIX_API_KEY. Our summary lists: Node.js; A credential in PHOENIX_API_KEY. Compatibility (from SKILL.md): Requires Node.js (for npx) or global install of @arizeai/phoenix-cli. Optionally requires jq for JSON processing..
SKILL.md contains no URLs. Its commands use npx and curl, which can reach the network depending on how they are called. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found notes only (mentions a .env file), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.
Phoenix CLI is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
About 6.8k tokens (SKILL.md is roughly 27k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 3.8k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Phoenix CLI: Agentsop HTTP Tool Wrapping (agentsope/SkillAlchemy, 459 stars), Phoenix CLI (github/awesome-copilot, 40k stars), Spider King (aoyunyang/spider-king-skill, 507 stars) and Build Error Adapter (ArcadeAI/arcade-mcp, 1k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Arize-ai (a GitHub organization) maintains it in Arize-ai/phoenix, which has 11,744 GitHub stars. The repository holds 39 skills in this directory. The repository was last updated on October 8, 2026.
Source: Arize-ai/phoenix on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.