Cotext

Honest comparison

How is Cotext different from
everything else?

There are several products in the AI-personalization space. They optimize for different things. Here's where each wins and where Cotext does.

ChatGPT Memory

Built into ChatGPT. Zero setup.
If you only use ChatGPT and trust OpenAI with what you tell it, ChatGPT Memory is fine. If you use multiple AIs or want the memory to live on your machine, you need something else.
›Strengths & trade-offs
Strengths
  • No install, no extension, no configuration.
  • Tightly integrated — OpenAI tunes it for their model.
  • Memories edit-able from the chat itself.
Trade-offs
  • Only works inside chatgpt.com. Switch to Claude or Gemini and you start over.
  • OpenAI sees and stores everything you tell it to remember.
  • No portability — you can't take memories with you.

Claude Projects

Per-project system prompts in Claude.
A great feature inside Claude. Cotext complements it: if you write a Claude Project prompt by hand and like it, you can publish it and share — and Cotext will learn refinements from how you actually react to responses.
›Strengths & trade-offs
Strengths
  • Pinpoint control over Claude's behavior per workspace.
  • Persists across conversations within a project.
  • Visible and editable from the Claude UI.
Trade-offs
  • Works only in Claude — same single-product wall as ChatGPT Memory.
  • Manual: you write the prompt yourself; Claude doesn't learn from your reactions.
  • Tied to your Anthropic account; Anthropic stores it.

Cursor Rules / .cursorrules

Per-repo rules for the Cursor IDE.
Cotext and Cursor Rules don't compete — they layer. Many users will keep both: Cursor Rules for repo-specific rules; Cotext for the personal style and preferences that should follow you everywhere.
›Strengths & trade-offs
Strengths
  • Lives next to the code; in source control with the project.
  • Cursor and the model see it on every interaction.
  • Granular per-repo customization is exactly the right scope for code work.
Trade-offs
  • Only applies inside Cursor.
  • Manual to write, manual to refine.
  • No cross-tool consistency: your Cursor rules don't carry to Claude Code, ChatGPT, or the API.

Sider / Monica / Merlin / et al.

Browser extensions that wrap multiple AIs.
Different trust posture: Sider et al. operate as a service with your conversations passing through them. Cotext runs entirely on your machine — synthesis happens via WebGPU or a local Ollama, and nothing leaves unless you click Publish. If you don't need that distinction, the commercial options are mature; if you do, that distinction is the whole point.
›Strengths & trade-offs
Strengths
  • Works across multiple AI sites, similar to Cotext.
  • Often add useful UX features — quick prompts, page summaries.
Trade-offs
  • Your prompts and responses route through their servers (often by design).
  • Closed source; the data flow is whatever they say it is.
  • Most charge a subscription.
  • USENIX Security '25 documented credential handling issues across this category — worth looking up before installing one.

Hand-written CLAUDE.md / AGENTS.md

A markdown file you maintain yourself.
The strongest realistic alternative for developers. Cotext's pitch is: you'd write the same file by hand, but having something watch your reactions and propose updates is faster and produces a more honest distillation. You can `cotext pull > CLAUDE.md` and you're done.
›Strengths & trade-offs
Strengths
  • Total control. You wrote every word, you trust every word.
  • Free, instant, and works with Claude Code, Cursor, the API, anything that injects markdown.
  • No infrastructure, no extension, no model.
Trade-offs
  • Drift: you write it once, it gets stale, you forget to update.
  • Cold-start: you don't know what to put in it until you've been frustrated by an AI a hundred times.
  • No portability across devices unless you sync the file yourself.

Claude Code Skills (SKILL.md)

Anthropic's mechanism for bundling capabilities into Claude Code.
Different layer, not a competitor. Skills are capability injection — “run my CRM migrator,” “use these design tokens.” Cotext is preference injection — “be terse, no preamble, cite sources.” Most users will want both: a `cotext` Skill could even wrap the MCP server so Claude Code calls `get_preferences` automatically. They compose cleanly.
›Strengths & trade-offs
Strengths
  • First-party — Anthropic ships and maintains it, so it's the canonical way to extend Claude Code.
  • Each skill is a folder with `SKILL.md` plus optional scripts; Claude reads descriptions and loads them when relevant.
  • Git-friendly — skills live in the repo, version with your code, and travel with the project.
Trade-offs
  • Claude Code only. Doesn't reach claude.ai, ChatGPT, Gemini, or the API surfaces those products use.
  • Capabilities, not preferences. A skill says “here's how to do X”; it doesn't encode “here's how I want every response styled.”
  • Manual to write. Claude won't infer a skill from your reactions — you author the file.
The wedge

Local-first, cross-tool, learning

The other tools each pick one of those three. ChatGPT Memory: cloud, single-tool, learning. Claude Projects: cloud, single-tool, manual. Cursor Rules: local, single-tool, manual. Sider: cloud, multi-tool, manual.

Cotext is the only thing in the category that does all three at once. Whether you want it depends on whether that combination matters to you.

When Cotext is the wrong tool
  • You only use one AI tool, ever — single-product memory is enough.
  • You like your hand-written CLAUDE.md and updating it monthly is fine.
  • You don't care where your data lives — convenience beats privacy for your use case.
  • You want a polished, supported product with a vendor on the other end of a phone.
We'd rather not waste your time. If any of the above describe you, the alternatives above are reasonable picks.

Ready to try?

Install CotextSee an example profile →