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 comet-ml/opik-skills --skill opik-diagnosegit clone --depth 1 https://github.com/comet-ml/opik-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/comet-ml/opik-skills/opik-diagnose)<a href="https://agentmods.dev/skills/comet-ml/opik-skills/opik-diagnose"><img src="https://agentmods.dev/badge/skills/comet-ml/opik-skills/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.
<a href="https://agentmods.dev/skills/comet-ml/opik-skills/opik-diagnose"><img src="https://agentmods.dev/badge/skills/comet-ml/opik-skills/opik-diagnose.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00174 | $0.03126 |
| Opus 5 | $0.00087 | $0.01563 |
| Sonnet 5 | $0.00035 | $0.00625 |
| Haiku 4.5 | $0.00017 | $0.00313 |
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 yesterday.
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.
This is a copy
100% identical to opik-diagnose — 43 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 144 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}>'}
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.
- yesterday Changed · +34 lines · +27 tokens per session 495b0c3a06a9
- 7d ago First seen · 110 lines · 147 tokens per session scan A 46a031622753
opik-diagnose is a skill published in the GitHub repository comet-ml/opik-skills (7 stars, last pushed 2d ago), licensed Apache-2.0. It adds 174 tokens to every session and 3,126 once invoked, about $0.0009 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to opik-diagnose, differing in 43 lines, and is treated as a copy.
Other skills, from other repositories
opik-diagnose
Surface the Opik traces worth a developer's attention, ranked by signal — Diagnostics issues first, then errors, failed tool calls, latency, regressions, and low online-eval scores. With the Opik MCP connected it lists the project's agentinsightsissue entities, offers to turn Diagnostics on when the project has it…
opik-explain
Root-cause a specific Opik trace, or a pattern across traces, and return a grounded explanation. Uses the hosted Opik MCP when it is connected, and falls back to SDK scripting otherwise. Returns the root cause, the evidence spans as clickable Opik UI links, and one suggested next step. Use for "why did this trace…
tracely
Instrument AI agents with Tracely and turn their production traces into CI gates. Use when the user mentions Tracely, tracely-ai, tracelysdk, the tracely CLI, or asks to trace/observe an AI agent, add LLM evaluators or LLM-as-a-judge columns, debug why a trace or conversation isn't showing up, wire agent regression…
opik-instrument
Add Opik tracing to an existing app and verify a real trace lands. Installs the Opik package, detects the language and LLM framework, adds the minimum tracing, runs a safe representative path, confirms a trace in Opik, and returns the trace link. Use for "instrument my code", "add opik tracing", "add observability"…
opik
Reference for the Opik SDK — tracing, span types, framework integrations, threads, and the prompt library (Python, TypeScript, REST). Use for "what span types exist", "how do I flush", "trackopenai", "add OpikTracer", "version a prompt". To instrument a repo end to end, use the opik-instrument skill.
opik-evaluate
Build an LLM evaluation and run it against your app, returning an experiment with scores. Covers datasets, LLM judges, RAG evaluation, synthetic data, error analysis, and validating evaluators against human labels. Use when the user wants to measure or improve AI product quality, or asks about evals, judges, or…