Share your experiences and questions about keeping Claude, Codex, DeepSeek Harness, GLM, and Kimi within their token limits. What tricks have worked for you?
What the source supports
The video explains token limits for Claude, Codex, DeepSeek Harness, GLM, and Kimi, covering input/output token costs, context‑rotation commands, prompt hygiene, system prompt design, sub‑agents, and subscription strategies.
Why it matters
This article translates the video’s practical advice into a structured guide, adds a clear step‑by‑step workflow, and provides a FAQ to address common uncertainties.
What is worth discussing
- Understand the difference between input and output tokens and how language choice affects cost.
- Use context‑rotation techniques like /clear, /compact, and side‑chat to keep conversations lean.
- Clean project metadata (MCP, skills, CLAUDE.md, AGENTS.md) to reduce prompt noise.
- Apply Project Index, Search First, Frugal Reading, and Deny Noise principles to craft efficient system prompts.
- Leverage sub‑agents for research, coding, and review to distribute token usage.
Tools mentioned
- Claude
- Codex
- DeepSeek Harness
- GLM
- Kimi
Public links from the description
Questions for the community
- Which context‑rotation commands have you found most effective?
- How do you balance prompt clarity with token economy?
Source
Как НИКОГДА не упираться в лимиты Claude, Codex, DeepSeek Harness, GLM, Kimi