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review-interface

Official

Self-contained human-review UIs for agent traces.

Data & Analytics#human-in-the-loop#jsonl#annotation#llm-evaluation#data-labeling#review-ui
AuthorMiosa-osa
Version1.0.0
Installs0

System Documentation

What problem does it solve?

Annotating and auditing AI agent outputs and execution traces can be tedious and error-prone. This Skill generates self-contained HTML review interfaces that run entirely in the browser, enabling rapid, offline human evaluation of LLM outputs, agent traces, and labeled data.

Core Features & Use Cases

  • Create configurable annotation interfaces for reviewing, labeling, and comparing results from AI agents and models.
  • Supports loading data from JSONL, side-by-side comparisons, trace reviews, and export of labeled results for downstream QA and gold-standard dataset creation.
  • Works offline as a single self-contained HTML file with inline CSS/JS and keyboard navigation for efficient human-in-the-loop workflows.

Quick Start

Run /review-interface with your data file to generate a self-contained HTML review UI.

Dependency Matrix

Required Modules

None required

Components

Standard package

💻 Claude Code Installation

Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.

Please help me install this Skill:
Name: review-interface
Download link: https://github.com/Miosa-osa/canopy/archive/main.zip#review-interface

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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