inno-code-survey

To map research ideas to code, this skill aggressively searches GitHub for missing components, clones candidate repositories, and verifies their relevance to your project. It compiles a detailed implementation report linking novel concepts to runnable code.

Code survey mapping analyzes acquired repositories and related papers to produce a comprehensive implementation report. It bridges the gap between theoretical research pipelines and concrete code by structuring the connection between concepts and their actual software implementations.

The repository acquisition pipeline requires the Python requests library to function. This dependency enables the automated searching, fetching, and cloning of GitHub repositories needed to build your code survey.

You run a two-phase workflow: Phase A acquires missing repositories by searching and cloning from GitHub, while Phase B performs the code survey mapping. This structured pipeline outputs acquired code repos and an updated implementation survey.

Yes, you can use it for specialized research components. The skill detects gaps in your current code coverage, specifically targeting novel or specialized ideas, and aggressively searches GitHub to find matching repositories.

The code survey pipeline generates three main outputs: acquired code repos, an updated preparation result, and a model survey. These structured outputs track progress and provide a detailed implementation mapping for your research.