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by smol-ai · Agent Tool · ★ 151
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2024 note: the binding for the logger doesnt work anymore even tho it used to - we don't super know why yet 🐤 smol logger A minimal viable logger for Prompt/LLM App Engineering. Use your IDE as Logging UI - a fast, simple, extensible, zero dependency Node.js logging tool. In App Development: a fast logging tool that uses the filesystem as Log UI. In Prompt Engineering: wrap and transform async calls to OpenAI etc to cleanly capture Prompt vs Response. CLI to export logs to for spreadsheet import. Spreadsheets are all you need for prompt engineering! In Production: easily extended to send logs to a log store like Logflare Short video demo: https://www.loom.com/share/ae818b7d058343c1ad6caf8deee2e430 Features By default, logs to both the terminal and local json files for easy navigation/versioning Automatically logs time elapsed, filepath, line number, order of log call Clear logs by deleting the folder (customizable) CLI to compile json logs to a file for spreadsheet import (e.g. Google Sheets, Excel, Quadratic) Wrap & transform async calls to capture Prompt vs Response pairs Extensible Persist the logs to a rem
| Stars | 151 |
| Forks | 12 |
| Language | TypeScript |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 63.618623480951/100 |
| Open Issues | 1 |
| Last Updated | 2024-03-28 |
| Created | 2023-06-17 |
| Platforms | node |
| Est. Tokens | ~21k |
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logger is 🐤 A minimal viable logger for Prompt/LLM Engineering. Use your IDE as Logging UI - a fast, simple, extensible, zero dependency Node.js logging tool that starts simple in development and is easily ext. It is categorized as a Agent Tool with 151 GitHub stars.
logger is primarily written in TypeScript.
You can find installation instructions and usage details in the logger GitHub repository at github.com/smol-ai/logger. The project has 151 stars and 12 forks, indicating an active community.
logger is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to logger on Agent Skills Hub include claude-plugins, tutor-skills. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
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