Files
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Click a file in the tree to view its contents.
Or try a preset prompt below to watch the agentic loop in action.
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Method
URL
Status
Size
Time
Where's My Context?
Model Settings
Reasoning Effort what do these settings do?
Reasoning effort controls how many thinking tokens the model spends before producing its final answer. Higher effort improves accuracy on hard problems at the cost of latency and token spend. Thinking tokens are billed but do not appear in the context bar above — budget for them separately.
| Level | Anthropic effort |
OpenAI reasoning.effort |
|---|---|---|
| Off | — | none — no thinking tokens |
| Low | low — ~1k think tokens |
low |
| Medium | medium |
medium (default for o-series) |
| High | high |
high |
| Max | max — up to 32k think tokens |
xhigh — Extreme Thinking mode |
Anthropic deprecated the explicit budget_tokens parameter in Claude 4.x in favour of this effort enum. The underlying mechanism is the same: the model generates a scratchpad of chain-of-thought tokens that are not returned to the caller but influence the final answer.
System Prompt
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AGENTS.md
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Skills
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Tool Definitions
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Tool Results
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Your Prompt
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Model Response
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Token counts are estimated (~4 chars per token). Actual counts vary by model tokenizer.
How AI Assistants Work
- Assemble context — system prompt + AGENTS.md, any invoked /tools, tool schemas
- Read your prompt — added to the context window
- Call the model — sends everything to the LLM
- Execute tools — model requests file reads, grep, edits
- Loop — tool results go back to the model for the next turn
- Respond — final answer with all context consumed