Agent skill · operations · affaan-m
parallel-execution-optimizer
Speed up a task by turning it into a dependency graph of parallel lanes with a lane matrix, batched reads and checks, write surfaces isolated by file, worktree, branch, or service, and a final verification table. Use when the user wants a task done much faster through parallel work, concurrent agents, batched tool calls, isolated worktrees, many independent verification lanes, or bounded homogeneous work that reuses shared preparation while record operations remain sequential, without losing correctness.
Why this skill is useful
Provides a structured approach to parallel execution that optimizes task completion speed while ensuring correctness, which the AI wouldn't reliably generate on its own.
What it needs
About 5k tokens when loaded. Last updated 2026-08-06. 238,342 stars on the source repository.
What this skill does
Parallel Execution Optimizer Use this skill when speed comes from doing independent work at the same time: repo inspection, file reads, API checks, browser checks, build/test lanes, deploy readbacks, or multi-worktree implementation passes. Also use it when homogeneous work repeats unchanged preparation between records, even if the record operations must remain sequential. Core Pattern Turn urgency into a dependency graph before acting. 1. Define the objective and done signal. 2. Split work into lanes. 3. Mark each lane as parallel, sequential, or gated. 4. Run independent reads/checks together. 5. Keep writes isolated by file, worktree, branch, service, or dataset. 6. Merge only after evidence shows the lanes are compatible. 7. End with a verification table, not a vague speed claim. Lane Matrix Before a large push, write a compact matrix: Only run lanes in parallel when their write surfaces do not collide. Execution Rules Batch file reads, searches, status checks, and metadata queries. Use isolated worktrees for large unrelated implementation lanes. Start long-running tests, builds, backfills, and deploys in separate sessions, then poll them deliberately. If a lane discovers a blocker that changes the plan, pause dependent lanes and update the matrix. Never let a background process outlive the turn unless the user explicitly asked for a continuing service. Do not parallelize destructive commands, migrations, writes to the same table, or live customer-impacting deploys without an explicit gate. Bounded Homogeneous Work Reuse preparation when a finite group of records shares accepted invariant inputs, such as a mapping and tool contract. This reduces repeated discovery and task setup; it does not require concurrent writes. 1. Define the bounded record set, owner-defined completion unit, ordering, exclusions, done signal, accepted mapping/contract version, and replanning conditions. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills affaan-m/parallel-execution-optimizer--51796e