TrajectoryRL
2 posts

TrajectoryRL
@TrajectoryRL
Reinforcement Learning as a Service for optimizing agent trajectories powered by Bittensor.
Palo Alto Присоединился Şubat 2026
5 Подписки402 Подписчики

Agents need tools to improve themselves.
We’re starting to build that layer on SN11.
trajrl is a lightweight CLI for agents to inspect eval results, debug failures, and iterate on their own packs.
Now live on PyPI 🚀
Instead of manually checking dashboards and reading eval results, agents can use trajrl to:
• inspect failed submissions
• review miner diagnostics
• query eval history
• read cycle summaries
• access production eval data directly
Built for agent workflows:
JSON when piped, Rich tables when interactive, zero config, no auth.
Coming in v0.3.0: full conversation logs in eval archives (`*_conversation.jsonl`)
Agents improving agents.
Install: pip install trajrl
Docs: github.com/trajectoryRL/t…
PyPI: pypi.org/project/trajrl/
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