2.5 KiB
2.5 KiB
summary, read_when
| summary | read_when | ||
|---|---|---|---|
| How Clawdbot builds prompt context and reports token usage + costs |
|
Token use & costs
Clawdbot tracks tokens, not characters. Tokens are model-specific, but most OpenAI-style models average ~4 characters per token for English text.
How the system prompt is built
Clawdbot assembles its own system prompt on every run. It includes:
- Tool list + short descriptions
- Skills list (only metadata; instructions are loaded on demand with
read) - Self-update instructions
- Workspace + bootstrap files (
AGENTS.md,SOUL.md,TOOLS.md,IDENTITY.md,USER.md,HEARTBEAT.md,BOOTSTRAP.mdwhen new) - Time (UTC + user timezone)
- Reply tags + heartbeat behavior
- Runtime metadata (host/OS/model/thinking)
See the full breakdown in System Prompt.
What counts in the context window
Everything the model receives counts toward the context limit:
- System prompt (all sections listed above)
- Conversation history (user + assistant messages)
- Tool calls and tool results
- Attachments/transcripts (images, audio, files)
- Compaction summaries and pruning artifacts
- Provider wrappers or safety headers (not visible, but still counted)
How to see current token usage
Use these in chat:
/status→ emoji‑rich status card with the session model, context usage, last response input/output tokens, and estimated cost (API key only)./cost on|off→ appends a per-response usage line to every reply.- Persists per session (stored as
responseUsage). - OAuth auth hides cost (tokens only).
- Persists per session (stored as
Other surfaces:
- TUI/Web TUI:
/status+/costare supported. - CLI:
clawdbot status --usageandclawdbot providers listshow provider quota windows (not per-response costs).
Cost estimation (when shown)
Costs are estimated from your model pricing config:
models.providers.<provider>.models[].cost
These are USD per 1M tokens for input, output, cacheRead, and
cacheWrite. If pricing is missing, Clawdbot shows tokens only. OAuth tokens
never show dollar cost.
Tips for reducing token pressure
- Use
/compactto summarize long sessions. - Trim large tool outputs in your workflows.
- Keep skill descriptions short (skill list is injected into the prompt).
- Prefer smaller models for verbose, exploratory work.
See Skills for the exact skill list overhead formula.