These run in every project of mine and are published on my CV.
AI-agent contract and learning pipeline
A single binding operating contract (AGENTS.md) mirrored to every AI coding tool (Claude Code, Copilot, OpenCode, Cursor, Windsurf, Codex, Aider) so the work stays repeatable regardless of which tool does it. On top of that a three-layer Obsidian knowledge vault (modules, sublists, specs) and architectural decisions as ADRs.
MarkdownObsidianNode.jsPythonADR
Why it matters: One contract mirrored to every tool keeps the work repeatable.
gromi-prompts: versioned prompt registry
Prompts are versioned artefacts rather than strings buried in code: YAML metadata, a version history and test cases that a CLI runs as evals and compares across versions.
PythonJSONL evalsYAMLCLIGitHub Packages
Why it matters: Prompts versioned and runnable as evals, like any other code.
myaitools: a self-growing tool library
Implements the LATM loop ("LLMs as Tool Makers"): recognise → specify → build → test → document → register → use. At session start the tool catalogue is injected into context; at task end a cheap local heuristic decides for free whether some subtask was worth capturing as a tool, and if so, a detached builder agent writes it with tests and registers it.
PythonBashClaude Code hooksJSON manifestpytest
Why it matters: Repeated subtasks turn into tested tools on their own.