a2
A Python agent that checks solutions externally and investigates reuse of verified executable skills. Development alpha.
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Overview
Question
Can a successful solution become a skill that can be reused on other tasks? a2 investigates this through data transformation tasks.
Working parts
The small Python agent combines tools, shared memory, output validation and executable skills. Current tasks include normalization, source matching, conflict handling and field projection. Skill candidates produced from successful solutions must pass external checks on independent inputs before being stored.
Evaluation
Frozen learned skills are compared on separate tasks with history-free solving, successful context examples, human-written skills and unrelated skills. Quality, latency, model/tool calls and observed token use are reported separately.
Status and limits
The source reviewed on 13 October 2026 describes a development alpha. The offline demo verifies and reuses human-written skills; it does not demonstrate model learning. A bounded live training run recorded verified skill families, but an incomplete development pilot showed no efficiency advantage. Frozen multi-seed evaluation and real-user validation remain open. Publishing this page does not mean the software package has been publicly released.
Source record
Based on the a2 README, architecture and evaluation documents reviewed on 13 October 2026. No new experiment was run.
Writing from this work
Why does a plan refuse to run?
Stopping before execution when a skill version changes in the a2 demo, and the distinction between code identity and correctness.
The same task, a different file tomorrow
Reuse with the same skills, exact-code matching and independent result checks in a two-day synthetic CRM/ERP demo.
a2’s first technical preview
The 0.1.0a1 release: inspectable data workflows, reusable skills and the explicit boundaries of the technical preview.
A task’s journey through a2
A two-record example tracing the contract, execution path, output checks and the record left at the end.
When should an agent stop?
Completion, repetition, shared budgets, uncertain actions and authorization in a2: what must we know before taking the next step?
Turning an idea into a working tool
Through a2: the distance between a verified solution, a reusable skill, and a completed task.