·trace-annotation-tool
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trace-annotation-tool

Generate a custom trace annotation web app for open coding during LLM error analysis. Use when the user wants to review LLM traces, annotate failures with freeform comments, and do first-pass qualitative labeling (open coding). Also use when the user mentions "annotate traces", "trace review tool", "open coding tool", "label traces", "build an annotation interface", "review LLM outputs", or wants to manually inspect pipeline traces before building a failure taxonomy. This skill produces a tailored Python web application using FastHTML, TailwindCSS, and HTMX.

4Installs·0Trend·@maragudk

Installation

$npx skills add https://github.com/maragudk/evals-skills --skill trace-annotation-tool

How to Install trace-annotation-tool

Quickly install trace-annotation-tool AI skill to your development environment via command line

  1. Open Terminal: Open your terminal or command line tool (Terminal, iTerm, Windows Terminal, etc.)
  2. Run Installation Command: Copy and run this command: npx skills add https://github.com/maragudk/evals-skills --skill trace-annotation-tool
  3. Verify Installation: Once installed, the skill will be automatically configured in your AI coding environment and ready to use in Claude Code, Cursor, or OpenClaw

Source: maragudk/evals-skills.

SKILL.md

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Generate a custom local web application for open coding of LLM traces — the first qualitative pass of error analysis in the Analyze phase of the evaluation lifecycle.

fields represent the user query, intermediate steps, tool calls, and final output.

Ask the user: "These are the default features. Do you want anything else before I generate the tool?" Then incorporate any additional requests.

Generate a custom trace annotation web app for open coding during LLM error analysis. Use when the user wants to review LLM traces, annotate failures with freeform comments, and do first-pass qualitative labeling (open coding). Also use when the user mentions "annotate traces", "trace review tool", "open coding tool", "label traces", "build an annotation interface", "review LLM outputs", or wants to manually inspect pipeline traces before building a failure taxonomy. This skill produces a tailored Python web application using FastHTML, TailwindCSS, and HTMX. Source: maragudk/evals-skills.

Facts (cite-ready)

Stable fields and commands for AI/search citations.

Install command
npx skills add https://github.com/maragudk/evals-skills --skill trace-annotation-tool
Category
{}Data Analysis
Verified
First Seen
2026-02-25
Updated
2026-03-10

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Quick answers

What is trace-annotation-tool?

Generate a custom trace annotation web app for open coding during LLM error analysis. Use when the user wants to review LLM traces, annotate failures with freeform comments, and do first-pass qualitative labeling (open coding). Also use when the user mentions "annotate traces", "trace review tool", "open coding tool", "label traces", "build an annotation interface", "review LLM outputs", or wants to manually inspect pipeline traces before building a failure taxonomy. This skill produces a tailored Python web application using FastHTML, TailwindCSS, and HTMX. Source: maragudk/evals-skills.

How do I install trace-annotation-tool?

Open your terminal or command line tool (Terminal, iTerm, Windows Terminal, etc.) Copy and run this command: npx skills add https://github.com/maragudk/evals-skills --skill trace-annotation-tool Once installed, the skill will be automatically configured in your AI coding environment and ready to use in Claude Code, Cursor, or OpenClaw

Where is the source repository?

https://github.com/maragudk/evals-skills

Details

Category
{}Data Analysis
Source
skills.sh
First Seen
2026-02-25