Acontext
Skill memory layer for AI agents that learns from runs and creates reusable Markdown skill files.
Opens acontext.io in a new tab.
How the 6.4 was reached
- Quality of output5/10
Open source with 3.7k stars and Markdown skill files; moderate adoption, no independent output evaluations. Source: github.com
- Ease of use7/10
pip install plus an API key, then create a learning space and attach a session; skills build automatically. Source: acontext.io
- Pricing value7/10
Apache-2.0 code is free, but setup needs an Acontext API key and no hosted pricing is published. Source: github.com
- API and integration quality7/10
Python and TypeScript clients with tools to list and read skills; Markdown export to ZIP for portability. Source: docs.acontext.io
- Solves the problem it claims to solve6/10
Docs describe recording runs as Markdown procedures; 3.7k stars show interest, but no independent proof that learned skills improve later runs. Source: docs.acontext.io
6.4/10 is the average of the five criterion scores above. The evidence comes from 3 different sources.Scores come from public evidence (the tool's own pages and documentation, and independent reviews); we do not test every tool hands-on. Scored 29 September 2026, on version 1 of our five-criteria scoring method.
Pricing
- Self-hosted deployment
- Core skill memory features
- GitHub integration
- Hosted service
- Dashboard interface
- Team collaboration
- Session backup
For the full list of what each plan includes, and current prices, see github.com.
Key Features
- Session capture and analysis
- Automatic skill distillation
- Markdown skill file generation
- Agent memory persistence
- Cloud and self-hosted options
Pros & Cons
Pros
- Human-readable skill files
- No embeddings required
- Portable across different agents
- Continuous learning loop
- Open source availability
Cons
- Early stage product
- Limited pricing transparency
- Requires integration setup
- Small community
- Documentation appears sparse
Acontext offers an interesting approach to AI agent memory through skill distillation into readable Markdown files. While the concept is promising for agent improvement over time, it's still early stage with limited documentation and unclear pricing for the cloud offering.
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