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-instrumentgit 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-instrument)<a href="https://agentmods.dev/skills/comet-ml/opik-skills/opik-instrument"><img src="https://agentmods.dev/badge/skills/comet-ml/opik-skills/opik-instrument/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-instrument"><img src="https://agentmods.dev/badge/skills/comet-ml/opik-skills/opik-instrument.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 | $0.00101 | $0.02677 |
| Opus 5 | $0.00051 | $0.01339 |
| Sonnet 5 | $0.00020 | $0.00535 |
| Haiku 4.5 | $0.00010 | $0.00268 |
Grade A, and why
opik-instrument 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 11d 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.
This is a copy
100% identical to opik-instrument — 0 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 — 135 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Instrument — Add Opik Tracing and Verify a Real Trace
Definition of done: a representative, safely-executed path produces a trace that is confirmed in Opik and a direct trace link is returned. If verification can't be completed safely or autonomously, stop at the first genuine blocker and return exactly one concrete next step. Code edits alone are not success.
Operate: opinionated in execution, conservative in code changes, automatic in routine decisions, uncompromising about verifying value — but never by running something unsafe.
Inputs
The entry point is just /opik-instrument (optionally /opik-instrument <path>). Infer everything else; treat these only as optional overrides the user may pass, never as required setup:
- target path (default: project root) · project name (default: inferred from the repo) · run command (default: an inferred safe path) ·
migrate_prompts(default: false).
Never turn inference into a questionnaire. Ask only when you hit a genuine, non-inferable blocker (see Blockers).
Activation — the only in-scope work
1. Configure Opik (one source of truth)
- If
~/.opik.configexists orOPIK_API_KEYis set, use it as-is. - Otherwise run the official flow:
opik configure(Python) /npx opik-ts configure(TypeScript). - Verify the config before instrumenting: run
opik healthcheck— it validates the config, the install, and backend/workspace reachability. If it fails, stop at that Blocker and fix config or connectivity before adding any tracing. - Only add project-local
.envvars if the project already uses that pattern. Never introduce a second config mechanism; never copy secret values between mechanisms.
2. Detect language & framework
Python (*.py, pyproject.toml) or TypeScript (*.ts, package.json). Identify the LLM framework from imports and pick its integration:
| Import | Integration |
|---|---|
openai / anthropic |
track_openai / track_anthropic |
langchain / langgraph |
OpikTracer callback |
crewai / dspy / google-genai / bedrock / llama_index / litellm |
track_crewai / OpikCallback / track_genai / track_bedrock / LlamaIndexCallbackHandler / OpikLogger |
TS: opik-openai / opik-vercel / opik-langchain |
trackOpenAI / OpikExporter / OpikCallbackHandler |
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.
- 11d ago First seen · 135 lines · 101 tokens per session scan A ac951dfe54c3
opik-instrument is a skill published in the GitHub repository comet-ml/opik-skills (7 stars, last pushed 2d ago), licensed Apache-2.0. It adds 101 tokens to every session and 2,677 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to opik-instrument, differing in 0 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-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-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…
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…
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…