opik-diagnose

opik-diagnose is a skill for Claude Code from comet-ml/opik-mcp. It costs 187 tokens per session (3,907 once invoked), scanned A, original, Apache-2.0.

A read-only diagnostic review of live Opik traces, which are records of how an AI application or agent ran. It ranks a short list of traces and diagnostic issues by signals such as errors, failed tool calls, slow response times, regressions, or low evaluation scores.

In plain words
What is it for?
Use it to find important traces for a project over a recent time window, such as errors today or unusually slow runs. It reports trace IDs and reasons for attention so another diagnostic step can investigate them.
Why use it?
It turns a large stream of production runs into a small set of problems worth investigating. This helps developers focus on real failures and performance issues without changing code.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: mentions Claude Code; mentions Codex.

Good fit Use it to find important traces for a project over a recent time window, such as errors today or unusually slow runs. It reports trace IDs and reasons for attention so another diagnostic step can investigate them.

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Install with agentmods
npx agentmods add skills/comet-ml/opik-mcp/opik-diagnose
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.

Any agent
npx skills add comet-ml/opik-mcp --skill opik-diagnose
Clone the repo
git clone --depth 1 https://github.com/comet-ml/opik-mcp

Made for: Claude Code.

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 opik-diagnose

README.md
[![agentmods](https://agentmods.dev/badge/skills/comet-ml/opik-mcp/opik-diagnose/github.svg)](https://agentmods.dev/skills/comet-ml/opik-mcp/opik-diagnose)
Your own site
<a href="https://agentmods.dev/skills/comet-ml/opik-mcp/opik-diagnose"><img src="https://agentmods.dev/badge/skills/comet-ml/opik-mcp/opik-diagnose/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.

agentmods 80×15 button for opik-diagnose

Your own site · 80×15
<a href="https://agentmods.dev/skills/comet-ml/opik-mcp/opik-diagnose"><img src="https://agentmods.dev/badge/skills/comet-ml/opik-mcp/opik-diagnose.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 187 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,907 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00187 $0.03907
Opus 5 $0.00093 $0.01954
Sonnet 5 $0.00037 $0.00781
Haiku 4.5 $0.00019 $0.00391

Measured today against content hash 2ef8ac6c435c, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

opik-diagnose 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 today.

The scan reads SKILL.md. This mod also ships 4 executable files (evals/fixtures/seed/seed.py, evals/grader.py, evals/metrics.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

src/opik_mcp/skills/opik-diagnose/SKILL.md · 177 lines

How it starts

The opening of the file, as written. The whole thing — 177 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Diagnose — Surface the Traces Worth Attention

Definition of done: a ranked shortlist of the online/production traces (and Diagnostics issues) worth attention, each carrying the signal that flagged it and its trace id, scoped to a project and a recent window, and ready to hand to /opik-explain. "Worth attention" means errored, slow, regressed, or low online-eval score — not a dump of every trace, and never offline experiment results. If the project can't be read, stop at the first genuine blocker and return one next step.

Operate: rank by real signal over live data, surface the few things worth a look, hand the top one to /opik-explain — and change no code. This skill is read-only by design.

Inputs

The entry point is /opik-diagnose (the current project), /opik-diagnose <project>, or /opik-diagnose <what to look for> (e.g. "slow traces", "errors today"). Infer the rest; treat these as optional overrides:

  • project (default: inferred from config/repo) · window (default: recent) · signal focus (default: all — errors, latency, regressions, low scores) · shortlist size (default: a handful).

Ask only at a genuine, non-inferable blocker (see Blockers).

Activation — the only in-scope work

1. Resolve scope

Project (from config/repo) + a recent window. Confirm Opik is reachable: if ~/.opik.config exists or OPIK_API_KEY is set, use it. Otherwise → Blocker ("run opik configure, then rerun").

2. Start from Diagnostics issues

Opik's Diagnostics already groups a project's recurring failures into ranked issues, each with a severity, occurrence counts, a cause, a suggested fix and example traces. Read that list first — it is the answer to "what is broken" the UI already computed, so do not rebuild it from raw traces.

With the Opik MCP connected, the agent_insights_issue entity is the primary path:

list('agent_insights_issue', project_name='<project>')        # open issues, ranked as the Diagnostics page ranks them
read('agent_insights_issue', '<issue id>', project_name='<project>')
#  → {issue: {name, cause, suggested_fix, severity, status, …}, example_trace_ids: [...], details: [...],
#     url: '<the issue's Diagnostics page>', trace_url_template: '<…/logs?trace={trace_id}>'}

Read the full file on GitHub · 177 lines

Files

What ships with it

8 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. today Changed · +33 lines · +13 tokens per session 2ef8ac6c435c
  2. 2d ago Changed · +34 lines · +27 tokens per session 495b0c3a06a9
  3. 11d ago First seen · 110 lines · 147 tokens per session scan A 46a031622753

Subscribe to this mod's changes

opik-diagnose is a skill published in the GitHub repository comet-ml/opik-mcp (217 stars, last pushed today), licensed Apache-2.0. It adds 187 tokens to every session and 3,907 once invoked, about $0.0009 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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