Condense Gauge tool note

Author: jacdevos

_posts/2026-05-13-executable-markdown-specs-agentic-coding.md

@@ -87,13 +87,7 @@ This is where BDD and AI fit together naturally: BDD plays at both ends of the f
 
 With AI, this matters more because LLMs amplify spec quality. Strong specs make autonomous execution more reliable. Weak specs create scalable incorrect behaviour.
 
-[Gauge](https://gauge.org/) test framework fits this BDD model well:
-
-* specs are Markdown-based
-* scenarios are human-readable and LLM-readable
-* executable scenarios are tied to code
-* Markdown lives naturally in the repo
-* CI can enforce the behaviour continuously
+[Gauge](https://gauge.org/) test framework fits this BDD model well because specs are Markdown-based, scenarios are human-readable and LLM-readable, executable scenarios are tied to code, Markdown lives naturally in the repo, and CI can enforce the behaviour continuously.
 
 Markdown itself becomes a superpower in LLM workflows. It is readable by humans, easy for LLMs to consume, reviewable in pull requests, and close enough to code to become part of the engineering system.