Traits — Teach your agent to code like you

Table of contentsI. The loop II. Two tools

Chapter I

The loop

Work with your agent. Context emerges from each conversation and correction.

As you work, your agent asks which insights to keep as traits. The traits that you approve become the context that guards the quality of your future work.

Decision models check subsequent code generation against all your traits, flagging ignored traits and nuances for the agent to fix.

Feedback Remember Review Correct

Observation 1 of 4

Tell the agent what you prefer.

Each correction is an opportunity to communicate your preferences for future codegen.

No more one-off requests. Keep lasting preferences.

Feedback

Chapter II

Two tools

Two MCP tools do the practical work. One curates the collection of traits while the other checks the code against the traits.

01 / Remember

`derive_trait`

Compare a proposed trait with the collection. A distinct trait can be saved and an existing trait can be reused or clarified. Confirmed conflicts lead to an explicit reconciliation approval.

Creation and changes require approval. Created, Updated, and Resolved include saved traits and their IDs.

A brass hand preserves a glowing seed of insight in an ivy-entwined archive of trait cards.

02 / Review

`check_traits`

Select files or glob patterns. The tool reviews current contents in 200-line chunks, compares them with the selected traits, and returns assessments that need attention.

Use traitNames for a focused review. Overlapping matches are deduplicated, while unmatched patterns review nothing.

An ornate brass lens examines a manuscript, revealing orderly botanical patterns among tangled threads.

GLOBAL DESLOPPIFICATION