Documentation Index
Fetch the complete documentation index at: https://docs.ardor.cloud/llms.txt
Use this file to discover all available pages before exploring further.
How Context Works
When conversations grow longer, they exceed the model’s context window limit:
To solve this, Cerebrum summarizes older messages to make room for new conversations:
Automatic Summarization
Cerebrum uses a sliding window with overlap approach. The overlap ensures context continuity - when summarizing, Cerebrum preserves context from the previous window so important connections aren’t lost.| Window | Messages | Overlap |
|---|---|---|
| 1 | 1, 2, 3 | — |
| 2 | 3, 4, 5, 6 | Message 3 from Window 1 |
| 3 | 6, 7, 8, 9 | Message 6 from Window 2 |
Summarization happens automatically in the background. You don’t need to do anything special.
What Gets Preserved
When Cerebrum summarizes context, it prioritizes:| Priority | Information Type | Example |
|---|---|---|
| Critical | Architecture decisions | ”Using PostgreSQL for the database” |
| Critical | Requirements from PRD | ”Must support 1000 concurrent users” |
| High | Service configurations | ”Backend runs on port 3000” |
| High | Current task context | ”Working on user authentication” |
| Medium | Previous solutions | ”Fixed CORS issue by adding headers” |
| Low | Exploratory discussions | ”Considered Redis but chose PostgreSQL” |
Best Practices
Reference the Canvas
Reference the Canvas
When context seems lost, ask Cerebrum to “look at the Canvas” - it shows the current environment, all services, and their configurations.
Check Environment State
Check Environment State
The Canvas displays the state of a specific environment. Make sure you’re looking at the right env (dev/staging/prod) when discussing changes.
Summarize Yourself
Summarize Yourself
For complex discussions, provide your own summary: “To recap, we decided to use X because Y.”
Break Into Sessions
Break Into Sessions
For very large projects, consider completing major milestones before moving on. This creates natural breakpoints.
Context Limits by Model
Different models have different context windows:| Model | Context Window |
|---|---|
| Gemini 3.1 Pro | 1M tokens |
| Gemini 3.5 Flash | 1M tokens |
| GPT-5.4 | 1.05M tokens |
| Grok 4.20 | 2M tokens |
| Claude Sonnet 4.6 | 200K tokens |
| Claude Opus 4.6 | 200K tokens |
| Claude Opus 4.7 | 1M tokens |
Larger context windows mean less frequent summarization, but all models benefit from Cerebrum’s smart context management.