aegis
Make AI coding agents architecture-aware: baseline-first, evidence-verified, drift-checked, and safe across long tasks.
9 results
Make AI coding agents architecture-aware: baseline-first, evidence-verified, drift-checked, and safe across long tasks.
Repository-root manifest for the DeepSeek Harness plugin that lives in extensions/dsh — the same package published to npm as dsh-deja. It re-exports the subdirectory so the plugin installs from a bare git URL or from github:vshulcz/deja-vu#path:extensions/dsh; the npm package is the shorter path. The repository itself is the Go project behind the deja binary.
Hindsight memory manager for DeepSeek Harness: settings UI (intranet/extranet routes) with automatic check & install of the official @vectorize-io/hindsight-coding-agents DSH adapter
Project Memory gives coding agents a single, trustworthy memory for a software repository — so they stop re-learning the same facts and stop writing conflicting "memory" files.
Git source-control sidebar for the DeepSeek Harness web UI: repo init, staging, commit/push/pull, branch & remote management, AI-generated Conventional Commits messages, and a commit-history graph.
Compare DeepSeek Harness, Codex, and Claude Code instruction surfaces for the same workspace.
Turn explicit coding-agent corrections into executable DeepSeek Harness regression tests.
Automatic, bounded type context and edit diagnostics for DeepSeek Harness
Local-first memory & context harness for coding agents