AI agent skills suite

PEA Skills Suite

The working practice behind the product stories: interpret the purpose, make a justified change, verify it and retain the decision record.

Workshop illustration connecting human intent, improvement, an audit trail and reflectionView full image
Method illustration · Not an application screenshot

One entry point, retained context

The suite makes Improve the normal entry point for bounded work. Intent interprets what the operator means before action; Trail records substantive decisions afterwards. Destination consolidates accepted direction when a durable choice needs settling, and Orient refreshes the map when accumulated evidence makes the old one misleading. The aim is not to make the operator manually orchestrate a roster of agents.

A destination is not unlimited authority

The operator remains responsible for purpose and consequential decisions. A delegated implementation task is not permission to buy services, change the destination, publish private material or erase evidence. The suite connects improvement to an explicit boundary and a prediction that can be checked. That distinction matters when showing fast product delivery: generated code alone does not establish that the right product was built or that its release works.

The machine in the illustration

The owner-selected workshop illustration makes the connected loop visible: human intent feeds the work, a decision trail passes through it, and reflection feeds learning back into later runs. It is an illustration of the method, not a screenshot of an executable orchestration service. The actual skill artifacts are readable Markdown intended for compatible agent hosts, with target-local memory and an append-only semantic trail.

Evidence and limitations

The three product overviews give bounded release timelines. They illustrate a practice but do not isolate the skills suite as the cause of delivery speed. An agent-authored trail is also not independent evidence of everything it claims. Optional harness capture serves a different trust layer, and external verification remains necessary for deployed behavior. Probe is separate research instrumentation, not a required step in ordinary development. See the repository for the current contracts, installation and historical evidence.

Application screen