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.
npx skills add boshi-xixixi/TraeSkill --skill arize-instrumentationgit clone --depth 1 https://github.com/boshi-xixixi/TraeSkillWrote 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.
[](https://agentmods.dev/skills/boshi-xixixi/traeskill/arize-instrumentation)<a href="https://agentmods.dev/skills/boshi-xixixi/traeskill/arize-instrumentation"><img src="https://agentmods.dev/badge/skills/boshi-xixixi/traeskill/arize-instrumentation/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/boshi-xixixi/traeskill/arize-instrumentation"><img src="https://agentmods.dev/badge/skills/boshi-xixixi/traeskill/arize-instrumentation.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00121 | $0.04934 |
| Opus 5 | $0.00060 | $0.02467 |
| Sonnet 5 | $0.00024 | $0.00987 |
| Haiku 4.5 | $0.00012 | $0.00493 |
Grade A, and why
arize-instrumentation 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 9d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- arize-instrumentation — 88% identical, 92 lines differ
How it starts
The opening of the file, as written. The whole thing — 240 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Arize Instrumentation Skill
Use this skill when the user wants to add Arize AX tracing to their application. Follow the two-phase, agent-assisted flow from the Agent-Assisted Tracing Setup and the Arize AX Tracing — Agent Setup Prompt.
Quick start (for the user)
If the user asks you to "set up tracing" or "instrument my app with Arize", you can start with:
Follow the instructions from https://arize.com/docs/PROMPT.md and ask me questions as needed.
Then execute the two phases below.
Core principles
- Prefer inspection over mutation — understand the codebase before changing it.
- Do not change business logic — tracing is purely additive.
- Use auto-instrumentation where available — add manual spans only for custom logic not covered by integrations.
- Follow existing code style and project conventions.
- Keep output concise and production-focused — do not generate extra documentation or summary files.
- NEVER embed literal credential values in generated code — always reference environment variables (e.g.,
os.environ["ARIZE_API_KEY"],process.env.ARIZE_API_KEY). This includes API keys, space IDs, and any other secrets. The user sets these in their own environment; the agent must never output raw secret values.
Phase 0: Environment preflight
Before changing code:
- Confirm the repo/service scope is clear. For monorepos, do not assume the whole repo should be instrumented.
- Identify the local runtime surface you will need for verification:
- package manager and app start command
- whether the app is long-running, server-based, or a short-lived CLI/script
- whether
axwill be needed for post-change verification
- Do NOT proactively check
axinstallation or version. Ifaxis needed for verification later, just run it when the time comes. If it fails, see references/ax-profiles.md. - Never silently replace a user-provided space ID, project name, or project ID. If the CLI, collector, and user input disagree, surface that mismatch as a concrete blocker.
What ships with it
1 file 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.
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.
- 9d ago First seen · 240 lines · 121 tokens per session scan A ca7d2708af15
arize-instrumentation is a skill published in the GitHub repository boshi-xixixi/TraeSkill (262 stars, last pushed 3mo ago), licensed MIT. It adds 121 tokens to every session and 4,934 once invoked, about $0.0006 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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