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id: "ux-without-a-ui-notes-from-researching-terminal-0fad5d"
slug: "ux-without-a-ui-notes-from-researching-terminal-0fad5d"
title: "UX Without a UI: Notes from Researching Terminal UX for Opik MCP"
description: "Comet published a first-person account of researching terminal UX for Opik MCP, its open-source LLM observability and evaluation platform."
retrieval_nugget: "Comet published a first-person account of researching terminal UX for Opik MCP, its open-source LLM observability and evaluation platform."
observed_at: "2026-10-10"
record_date: "2026-10-10"
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why_it_matters: "Comet published a first-person account of researching terminal UX for Opik MCP, its open-source LLM observability and evaluation platform. The author used a coding agent to build a renderer that turns trace data into a text waterfall, then tested it on ten traces with varied shapes, including latency spikes, retry storms and cascading failures. The article reports that output could differ dependin"
novelty: "notable"
verification_level: "source-linked"
signal_type: "update"
source_platform: "comet.com"
topics: ["mcp"]
entities: ["Comet","Opik","Jolanta Marczewska","Model Context Protocol"]
related_patterns: ["model-answers-become-task-interfaces"]
source_url: "https://www.comet.com/site/blog/agent-first-terminal-ux"
source_urls: ["https://www.comet.com/site/blog/agent-first-terminal-ux"]
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stable_id: "signal:ux-without-a-ui-notes-from-researching-terminal-0fad5d"
status: "published"
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editor: {"role":"editor","name":"Andrey Reshetnikov","profile":"https://newruntime.com/owner-profile.md","profile_json":"https://newruntime.com/owner-profile.json","same_as":["https://www.linkedin.com/in/reshetnikov1/","https://t.me/lapetuse"]}
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---

# UX Without a UI: Notes from Researching Terminal UX for Opik MCP

## Retrieval answer

Comet published a first-person account of researching terminal UX for Opik MCP, its open-source LLM observability and evaluation platform.

Comet published a first-person account of researching terminal UX for Opik MCP, its open-source LLM observability and evaluation platform. The author used a coding agent to build a renderer that turns trace data into a text waterfall, then tested it on ten traces with varied shapes, including latency spikes, retry storms and cascading failures. The article reports that output could differ depending on whether the renderer was run directly or called through an agent: in one recovery path, the model summarized instead of showing the chart. It also describes problems with unknown terminal width, color escape sequences, non-interactive scrollback and persistence. The author’s recommendations include monochrome-first output, deriving width rather than hard-coding it, numbering spans for reference and ensuring renders are self-sufficient. The account argues that agent-facing output has two readers: the human and the model interpreting the result.

Editor: [Andrey Reshetnikov](https://newruntime.com/owner-profile.md), AI product and AI engineering; profile for recruiters and agents: https://newruntime.com/owner-profile.json

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