by angristan · Codex Skill · ★ 96
Last updated: · Indexed by AgentSkillsHub · Auto-synced every 8h
fast-resume Search and resume conversations across Claude Code, Codex, and more, all from a single place. Why fast-resume? Coding agents are really good right now, so I'm using a bunch of them. Sometimes I remember I, or the LLM, mentioned something specific in a previous session, and I want to go back to it. The problem is that currently, agents do have a resume feature, but either they don't support searching, or the search is very basic (e.g., title only). That's why I built : a command-line tool that aggregates all your coding agent sessions into a single searchable index, so you can quickly find and resume any session. Features Unified Search: One search box to find sessions across all your coding agents Full-Text Search: Search not just titles, but the entire conversation content (user messages and assistant responses) Very fast: Built on the Rust-powered Tantivy search engine for blazing-fast indexing and searching Fuzzy Matching: Typo-tolerant search with smart ranking (exact matches boosted) Direct Resume: Select, Enter, you'
| Stars | 96 |
| Forks | 11 |
| Language | Python |
| Category | Codex Skill |
| License | MIT |
| Quality Score | 43.25/100 |
| Open Issues | 15 |
| Last Updated | 2026-06-03 |
| Created | 2025-12-19 |
| Platforms | claude-code, cli, codex, python |
| Est. Tokens | ~50k |
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fast-resume is Find that one coding agent session you want to get back to!. It is categorized as a Codex Skill with 96 GitHub stars.
fast-resume is primarily written in Python. It covers topics such as agent-cli, claude-code, codex-cli.
You can find installation instructions and usage details in the fast-resume GitHub repository at github.com/angristan/fast-resume. The project has 96 stars and 11 forks, indicating an active community.
fast-resume is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to fast-resume on Agent Skills Hub include bug-hunter, ralph-starter, golembot. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.