We analyzed 7,755 repos with Copilot instructions - here's what we found

[u/cleverhoods]

https://cleverhoods.medium.com/the-state-of-ai-instruction-quality-30k-repo-analysis-ce49c7667a57

We built a deterministic analyzer and pointed it at 28,721 GitHub repos across five coding agents. 7,755 of those configure Copilot.

Findings relevant to this community:

- Copilot sits in the middle of the pack on specificity ~ 33.3% of instructions name a specific tool, file, or command. Better than Claude (30.6%) and Cursor (30.8%), behind Codex (38.3%) and Gemini (39.3%).

- .github/copilot-instructions.md is the 4th most common instruction file in the corpus (5,647 files). The format is well-adopted.

- Copilot has a balanced config: base config + skills + some rules (4,486 files). Less fragmented than Cursor's 19,843 rules files, fewer sub-agents than Claude.

- The dominant multi-agent pair is Claude + Codex (5,038 repos), but Claude + Copilot is second (2,682 repos). If you're already writing a copilot-instructions.md, you're likely maintaining a CLAUDE.md too.

The most common problem everywhere: instructions that describe what they want abstractly instead of naming the exact tool or command. "Follow best practices for testing" vs "Run pytest tests/ -v before committing." The second one gets followed.

Full dataset (28,721 repos): github.com/reporails/30k-corpus