arize-annotation

arize-annotation is a skill for Claude Code, Codex from boshi-xixixi/TraeSkill. It costs 97 tokens per session (2,522 once invoked), scanned A, original, MIT.

A guide for setting up and using human-review labels and review queues in Arize, a platform for monitoring and evaluating AI systems. Labels can be categories, numbers, or free-text notes attached to recorded AI activity and examples.

In plain words
What is it for?
Use it to create label definitions and review queues, or apply labels to Arize records through the command line or Python SDK.
Why use it?
It organizes human feedback so teams can consistently review AI results and investigate project records.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: installed under .agents/ (shared by several agents).

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/boshi-xixixi/traeskill/arize-annotation
Any agent
npx skills add boshi-xixixi/TraeSkill --skill arize-annotation
Clone the repo
git clone --depth 1 https://github.com/boshi-xixixi/TraeSkill

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for arize-annotation

README.md
[![agentmods](https://agentmods.dev/badge/skills/boshi-xixixi/traeskill/arize-annotation.svg)](https://agentmods.dev/skills/boshi-xixixi/traeskill/arize-annotation)
Your own site
<a href="https://agentmods.dev/skills/boshi-xixixi/traeskill/arize-annotation"><img src="https://agentmods.dev/badge/skills/boshi-xixixi/traeskill/arize-annotation.svg" alt="Measured on agentmods" height="20"></a>
Per session 97 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,522 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00097 $0.02522
Opus 5 $0.00048 $0.01261
Sonnet 5 $0.00019 $0.00504
Haiku 4.5 $0.00010 $0.00252

Measured 6d ago against content hash 1847dd04c927, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

Grade A, and why

arize-annotation scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.trae/Skills/.agents/skills/arize-annotation/SKILL.md · 297 lines

How it starts

The opening of the file, as written. The whole thing — 297 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Arize Annotation Skill

SPACE — All --space flags and the ARIZE_SPACE env var accept a space name (e.g., my-workspace) or a base64 space ID (e.g., U3BhY2U6...). Find yours with ax spaces list.

This skill covers annotation configs (the label schema) and annotation queues (human review workflows), as well as programmatically annotating project spans via the Python SDK.

Direction: Human labeling in Arize attaches values defined by configs to spans, dataset examples, experiment-related records, and queue items in the product UI. This skill covers: ax annotation-configs, ax annotation-queues, and bulk span updates with ArizeClient.spans.update_annotations.


Prerequisites

Proceed directly with the task — run the ax command you need. Do NOT check versions, env vars, or profiles upfront.

If an ax command fails, troubleshoot based on the error:

  • command not found or version error → see references/ax-setup.md
  • 401 Unauthorized / missing API key → run ax profiles show to inspect the current profile. If the profile is missing or the API key is wrong, follow references/ax-profiles.md to create/update it. If the user doesn't have their key, direct them to https://app.arize.com/admin > API Keys
  • Space unknown → run ax spaces list to pick by name, or ask the user
  • Security: Never read .env files or search the filesystem for credentials. Use ax profiles for Arize credentials and ax ai-integrations for LLM provider keys. If credentials are not available through these channels, ask the user.

Concepts

What is an Annotation Config?

An annotation config defines the schema for a single type of human feedback label. Before anyone can annotate a span, dataset record, experiment output, or queue item, a config must exist for that label in the space.

Field Description
Name Descriptive identifier (e.g. Correctness, Helpfulness). Must be unique within the space.
Type categorical (pick from a list), continuous (numeric range), or freeform (free text).
Values For categorical: array of {"label": str, "score": number} pairs.
Min/Max Score For continuous: numeric bounds.
Optimization Direction Whether higher scores are better (maximize) or worse (minimize). Used to render trends in the UI.

Read the full file on GitHub · 297 lines

Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 6d ago First seen · 297 lines · 97 tokens per session scan A 1847dd04c927

Subscribe to this mod's changes

arize-annotation is a skill published in the GitHub repository boshi-xixixi/TraeSkill (261 stars, last pushed 3mo ago), licensed MIT. It adds 97 tokens to every session and 2,522 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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