ratel-ai / ratel
Context engineering for AI agents. ~80% fewer tokens. Fix tool overload. Skills and memory with in-process BM25 and semantic retrieval. Progressive Disclosure. No vector DB.
Why this job: says: context engineering; topics: memory
What it does
The context engineering layer for AI agents. Selects only the tools and skills relevant to each turn, recovering accuracy lost to tool overload and cutting what you pay per call. No vector DB, no infra.
Get started
No single install command. Read the steps in the README (opens in new tab)
- Maintenance
- Active
- Last commit 7 days ago
- Stars
- 554
- +7 this week
- Licence
- MIT
- Allows business use
- Downloads for
- None listed
- No release files
- Latest tag
- vercel-ai-sdk-v0.5.0
- Released 2 months ago
- Built with
- Rust
- 40% of the code
Is it looked after?
- Contributors
- 6
- Last 90 days
- Issues
- 65% closed
- 8 still open
- Pull requests
- 192 merged
- 6 waiting
- Releases
- 158
- 30+ in the last year
- Contributing guide (opens in new tab)
- No security policy
- Code of conduct (opens in new tab)
Similar repos
| Repo | Stars | Last commit | Licence | Downloads for |
|---|---|---|---|---|
| mordang7 / ContextKeep | 159 | 52 days ago | MIT | No downloads |
More: languages, topics and project record
Languages
- Rust 40%
- TypeScript 35%
- Python 22%
- JavaScript 2%
Topics
- accuracy
- agents
- claude-skills
- context
- harness
- llm
- llm-routing
- mcp
- mcp-server
- memory
- optimization
- rag
Project record
- JobAgent memory
- StatusFeatured
- Commits165
- Forks32
- Watching2
- Stars in 28 days+84
- CreatedNov 12, 2025
- First seen by usNov 7, 2026
- CheckedNov 9, 2026