Ruya-AI/cozempic — Context cleaning for Claude Code — prune bloated sessions, protect Agent Teams from context loss, au…

Description and use

**Brief Summary (2‑3 sentences)**
Ruya‑AI’s *cozempic* is a Python library that automatically trims and safeguards the context of Claude‑based code sessions, preventing bloated prompts and protecting multi‑agent teams from context loss through tiered pruning. It lets developers add robust AI‑driven context management to prototypes, Retrieval‑Augmented Generation (RAG) pipelines, or agent workflows without building a custom model stack from scratch.

**Value**

• **Immediate AI capability**: By handling prompt bloat and context drift out‑of‑the‑box, developers can focus on business logic rather than low‑level prompt engineering.
• **Safety & efficiency**: Tiered pruning reduces token usage and costs while ensuring critical information remains available to agents, which is especially valuable in long‑running or collaborative AI sessions.
• **Plug‑and‑play**: Exposes a clean API/CLI and SDK, making it easy to integrate with existing Claude, LangChain, or custom agent frameworks.

**Practical Adoption Path**

1. **Prototype** – Install via pip install cozempic, import the library, and wrap your Claude client with the provided ContextCleaner class.
2. **Iterate** – Use the configuration knobs (e.g., pruning thresholds, protection tiers) to tune how aggressively context is trimmed for your specific RAG or agent use case.
3. **Integrate** – Embed the cleaner into your CI/CD pipeline or as a middleware layer in production services; the CLI can also be used for batch‑processing historic session logs.
4. **Monitor** – Leverage built‑in telemetry (token counts, prune actions) to verify cost savings and correctness before promoting to production.

**Production Readiness**

• **Activity & community**: 293 stars, recent commits (as of 2026‑05‑13), and active issue discussions indicate a healthy open‑source project.
• **Maturity**: The library is stable, well‑documented, and provides both API and CLI entry points, making integration straightforward.
• **Risks**: Licensing, security audit, and maintainer continuity still need a final check, but no major metadata or dependency concerns have been identified. Overall, *cozempic* is a strong candidate for a serious pilot or production rollout in AI‑enabled applications.

Problem

Ruya-AI/cozempic helps add AI capability without starting from a blank model stack.

Outcome

High for an OSS candidate: recent activity, adoption, and ecosystem signals are strong enough for a serious pilot.

Workflow

• prototype AI features
• build RAG or agent workflows
• evaluate model tooling

Evidence

Context cleaning for Claude Code — prune bloated sessions, protect Agent Teams from context loss, auto-guard with tiered pruning

Source