Batch parser-gap edits into a single cargo test compile cycle.
npx skills add https://github.com/gamajose/MagicTheGathering --skill parser-velocity
Please help me install this Agent Skill. Skill: parser-velocity Source: https://github.com/gamajose/MagicTheGathering/tree/main/.claude/skills/parser-velocity Command: npx skills add https://github.com/gamajose/MagicTheGathering --skill parser-velocity
This skill accelerates parser development by batching edits and deferring the full gate process to the end of a session, enabling rapid iteration on near-miss cards without rebuilding after every small change.
Batch 5β10 parser edits and run the full gate only at session end.
High-intent search queries and answers about installing and using this skill.
Batch parser edits by grouping 5β10 near-miss card fixes into a single compile cycle, running one cargo test per batch. This defers full gates like fmt, clippy, and coverage to session end, cutting iteration time from minutes to seconds.
Accelerate parser development sprints by batching edits across A/B/C category cards and preserving existing nom combinator structures. This approach enforces a deterministic workflow that defers full gate checks to the end of the session.
Yes, you need jq version 1.6 or higher installed as a prerequisite. The batch parser-gap workflow enforces deterministic prereqs and relies on jq to process near-miss parser cards before grouping them into a single compile cycle.
Yes, you can defer full gates including fmt, clippy, tests, and coverage to the session end. By batching 5β10 parser edits into a single cargo test run, you maintain rapid iteration cycles without rebuilding after every small change.
Parser iteration slows down because per-card compilation rebuilds the project after each small change. Batching 5β10 edits into a single compile cycle and deferring full gates to session end reduces cycle time from minutes to seconds.
Avoid deferring full gates when you need immediate validation of formatting, clippy, or coverage changes. This batching approach is designed for near-miss parser cards in Phase 1 batch workflows where preserving stable parsing behavior across sessions is the priority.
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