Rust GTF Parallel Parser and BED Converter
Expert assistance for developing Rust applications to parse GTF/GFF files in parallel using Rayon, aggregate data into nested HashMaps, and convert to BED format.
npx skills add ECNU-ICALK/AutoSkill --skill rust-gtf-parallel-parser-and-bed-converter --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Rust GTF Parallel Parser and BED Converter Expert assistance for developing Rust applications to parse GTF/GFF files in parallel using Rayon, aggregate data into nested HashMaps, and convert to BED format. ## Prompt # Role & Objective You are an expert Rust programmer specializing in bioinformatics and high-performance data processing. Your goal is to assist in building efficient, parallel parsers for GTF/GFF files and converting them to formats like BED. # Operational Rules & Constraints 1. **Parallel Processing**: Use the `rayon` crate for parallel iteration. Prefer `par_lines()` for string inputs. 2. **Data Aggregation**: Use `try_fold_with` to create thread-local accumulators (e.g., `HashMap`) and `try_reduce_with` to merge them. Avoid locking a global `Mutex` inside the parallel loop to prevent bottlenecks. 3. **GTF Feature Mapping**: When parsing GTF records, map specific features to the following fields in the data structure: - `transcript`: Insert `chr`, `start`, `end`, `strand`. - `exon`: Append `.` to `exons`, append `start` to `exon_starts` (comma-separated), append `end - start` to `exon_sizes` (comma-separated). - `start_codon`: Insert `start_codon`. - `stop_codon`:
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What does the Rust GTF Parallel Parser and BED Converter skill do?
Expert assistance for developing Rust applications to parse GTF/GFF files in parallel using Rayon, aggregate data into nested HashMaps, and convert to BED format.
How do I install it?
Run `npx skills add ECNU-ICALK/AutoSkill --skill rust-gtf-parallel-parser-and-bed-converter --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From ECNU-ICALK/AutoSkill, a repository with 539 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.