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 Arize-ai/arize-skills --skill arize-instrumentation-healthgit clone --depth 1 https://github.com/Arize-ai/arize-skillsWrote 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/arize-ai/arize-skills/arize-instrumentation-health)<a href="https://agentmods.dev/skills/arize-ai/arize-skills/arize-instrumentation-health"><img src="https://agentmods.dev/badge/skills/arize-ai/arize-skills/arize-instrumentation-health/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/arize-ai/arize-skills/arize-instrumentation-health"><img src="https://agentmods.dev/badge/skills/arize-ai/arize-skills/arize-instrumentation-health.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk warn
- 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 | $0.00113 | $0.01178 |
| Opus 5 | $0.00056 | $0.00589 |
| Sonnet 5 | $0.00023 | $0.00236 |
| Haiku 4.5 | $0.00011 | $0.00118 |
Grade A, and why
arize-instrumentation-health 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 12d 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.
How it starts
The opening of the file, as written. The whole thing — 66 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Arize Instrumentation Health Skill
Use this skill for an on-demand instrumentation health audit over a project's existing traces — the aggregate counterpart to arize-instrumentation (which verifies a single new trace) and arize-trace (which exports and inspects spans). It answers questions like:
- "Why do my traces look empty or flat?"
- "Check whether my Arize instrumentation is healthy."
- "Find instrumentation issues in this project."
- "Why are my evals / token / cost dashboards showing n/a or zero?"
Workflow
- Resolve scope — get the project (and space, if needed). If ambiguous, ask; do not guess.
- Export a bounded span sample using the
arize-traceskill — do not hand-rollaxflags here. Follow its export guidance: start with a small sample scoped by--start-timeto a recent window, into--output-dir .arize-tmp-traces. Pull ~20 traces' worth of spans for a full audit (see minimum-data rules below). - Group spans by trace (
context.trace_id); within each trace identify the root (parent_id/parent_span_idis null). - Run the deterministic checks in references/checks.md against the sample.
- Report findings ranked by severity then confidence, using the Output format in references/checks.md.
This skill is read-only by default. Inspect exported spans and source files only when they help attribute the cause. Do not edit application code, tests, configuration, dependencies, or generated artifacts during a health audit unless the user explicitly asks this skill to make fixes in the same turn. When fixes are needed and the user has not asked for them in this turn, report the next action as a handoff to arize-instrumentation or the relevant framework-specific instrumentation path.
Reading exported spans
Attribute and column semantics (span kind, input.value/output.value, llm.token_count.*, status_code, parent_id, session.id) are documented in the arize-trace skill's Span Column Reference — use it rather than re-deriving field names.
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.
- 12d ago First seen · 66 lines · 113 tokens per session scan A fc0845ba0833
arize-instrumentation-health is a skill published in the GitHub repository Arize-ai/arize-skills (50 stars, last pushed yesterday), licensed MIT. It adds 113 tokens to every session and 1,178 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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