codegraph
An AI agent skill from QwenLM/qwen-code, scored 57 out of 100 by code.
Code score by group
It loses the most points in Done criteria (15), the group that checks whether there is a checklist and a step that verifies the work.
What the author says it does
Analyze indexed codebases via graph database (neug) and vector index (zvec). Covers call graphs, dependencies, dead code, hotspots, module coupling, architecture reports, semantic search, impact analysis, bug root cause from GitHub issues, class diagrams (UML), and PR review (risk scoring, conflict detection, auto-merge candidates, labeling). Also covers creating, inspecting, and repairing a CodeScope index. Use for: code structure, who calls what, why something changed, similar functions, module boundaries, bug tracing, class relationships, PR risk/conflicts, or any question benefiting from…
This is the description in the skill's own SKILL.md, written by its author, not by SkillCheatSheet.
- Repository
- QwenLM/qwen-code
- Folder
- .qwen/skills/codegraph
- License
- Apache-2.0
- GitHub stars
- 29,507
- SKILL.md lines
- 658
- Other files
- 5
Add codegraph to your agent
npx skills add QwenLM/qwen-code --skill codegraph
The command uses the open skills CLI. A skill is instructions and scripts your agent will follow, so read it first: open the folder on GitHub at the commit that was scored.
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All skills in QwenLM/qwen-code
Scores come from a snapshot of 300 public GitHub repositories taken on 12 November 2026. Every score is the result of fixed checks run by code; no AI is involved. How scoring works.