Context window fit check

Nearby workflows on Toolcore

• LLM token estimate — Rough character-based token planning for prompts and context—CJK-aware heuristic, browser-only—not tokenizer-exact. when you want a second pass with AI-assisted explanation on Toolcore.
• LLM context split & budget — Split pasted prompt blocks by a delimiter and see per-section rough token share and optional budget compare—browser-only, not tokenizer-exact. when you want a second pass with AI-assisted explanation on Toolcore.
• Long text chunker for chat paste — Split long pasted prose into sequential under-the-limit blocks—paragraph, line, or fixed character breaks—browser-only; not tokenizer-exact. when you want a second pass with AI-assisted explanation on Toolcore.
• LLM character budget from token cap — Plan max paste characters from a target token budget—same CJK-aware heuristic as token estimate, browser-only, not tokenizer-exact. when you want a second pass with AI-assisted explanation on Toolcore.

Common use cases

• Check if a RAG bundle plus system prompt still fits a 128K window before sending.
• Switch between 8K, 32K, and 200K presets when comparing model tiers.
• Spot overflow early and trim with long text chunker or whitespace savings.

Common mistakes to avoid

• Ignoring tool definitions and image tokens

  This counts pasted text only—reserve extra budget for tools, JSON schema, and vision payloads.

• Assuming 100% fill is safe

  Leave headroom for the model reply and tokenizer drift; aim below ~85% for drafts.

FAQ