Menu

Individual skill

context-window-design

0upvotes

Designing around token limits, memory, and conversation persistence.

claude-plugin/model-interaction-design/skills/context-window-design/SKILL.md

Read pinned source

Source commit f41b650435b62dec6d5b1dc3598ac4679f8b7ae7

What was checked

Matches the observed repository HEAD
Yes
Scanner rules are current
No
Repository scan complete
No
Skill scan complete
Yes
Observed behavior
Not checked yet
Last checked
Nov 7, 2026

These are observations at the recorded commit, not a guarantee of safety. Review the source before running it.

Install this skill

Choose an agent in your Stack or copy a command below. Commands fetch the pinned commit and copy only this skill directory. Existing destinations are refused. Copying a command does not install anything.

An install command is unavailable: current rules, complete repository and skill scans, an eligible behavior level and a permitted license are required.

Repository context

Repository stars (not skill ratings)
202
Repository last updated
Jun 9, 2026
License
MIT

Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.

Files and excerpt

File metadata and permitted, redacted excerpts come from the recorded scan. Source links are pinned to that commit.

Browse files
Read excerpt
# Context Window Design
Every AI model has a finite context window. Designing within this constraint — and designing the user experience around it — is a core skill for AI product design.
## The Context Window as a Design Material
The context window is not just a technical limitation. It's a design material:
- **What goes in**: System prompts, conversation history, retrieved documents, tool results, user preferences
- **What gets dropped**: Older messages, less relevant context, verbose instructions
- **What the user sees**: The conversation as presented may differ from what the model actually processes
Designers must understand context window allocation to design reliable experiences.
## Memory and Persistence
Users expect AI to remember. Design for different memory horizons:
- **Within-conversation memory**: What was said earlier in this chat. Usually handled by the context window itself.
- **Cross-conversation memory**: Preferences, past decisions, ongoing projects. Requires explicit memory systems.
- **Shared memory**: Context shared across multiple users or agents. Requires careful privacy design.
## Strategies for Limited Context
- **Summarisation**: Compress earlier conversation into summaries to free up tokens
Back to top