Spec-shaker – "Chaos engineering" for tests via semantic mutation
LLM-driven semantic mutants (off-by-one bugs, swallowed errors) beat mechanical swap mutation testing.
GRID is a small framework for working with coding agents
Process document for AI agent workflows, not a shipped tool.
Developers using AI coding agents with spec-driven workflows
LLM-driven semantic mutants (off-by-one bugs, swallowed errors) beat mechanical swap mutation testing.
Scores ambiguous specs before AI agents waste hours building the wrong thing.
Spec extraction from vibe-coded apps via reverse engineering—ambitious, but early and single-integration.
Spec-first workflow for AI agents when Cursor and Kiro already handle context.
Adds structure layer to AI agents: +9pp pass rate, 93% fault localization on SWE-bench.
Turns fuzzy AI prompts into a lightweight contract: SIGNATURE, BEHAVIOR (WHEN/THEN) and TESTS can be written as .rune YAML or embedded Markdown, letting any model or language generate the same behavior. Clever, low-friction idea with practical utilities (drift detection, reverse-engineer skills), but it’s a pattern rather than a product — adoption will hinge on tooling and CI integrations to make these specs enforceable at scale.