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github.com
About autocontext
autocontext is a harness for agent improvement. It runs tasks against evaluation, keeps useful lessons, discards dead ends, and leaves traces, reports, playbooks, datasets, and optional local-model training artifacts for the next run.
Description summarised by AI from the sources listed below.
Key features
- recursive self-improving harness
- task evaluation
- useful lesson keeping
- dead end discarding
- traces, reports, playbooks, datasets, and local-model training artifacts
Use cases
- agent improvement
- task automation
Pricing
Pricing model: Unknown — we have not been able to confirm pricing from the official website, so nothing is stated here.
Pricing summarised by AI from the sources listed below.
