lading: Skill for Claude Code

Optimization Submit Workflow

Complete optimization workflow with git automation. This skill wraps /lading-optimize-hunt and handles:

• Git branch creation
• Git commit with formatted results
• Optional push and PR creation

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Phase 0: Pre-flight

Run /lading-preflight first to ensure environment is ready.

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Phase 1: Prepare Git Environment

# Ensure clean state on main
git checkout main && git pull

# Verify clean working directory
git status

STOP if working directory is dirty. Commit or stash changes before proceeding.

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Phase 2: Hunt

Run /lading-optimize-hunt.

CRITICAL: After /lading-optimize-hunt completes, you MUST return here to Phase 3.

The hunt workflow will:

• Select and analyze optimization targets
• Capture baseline benchmarks
• Implement optimization
• Run basic ci/validate check
• Invoke /lading-optimize-review (which runs post-change benchmarks and judges)

The hunt will:

• Record the verdict in .claude/skills/lading-optimize-hunt/assets/db.yaml after review returns

BUT the hunt does NOT:

• Run post-change benchmarks (review does this)
• Make pass/fail decisions (review does this)
• Create git branches
• Commit changes
• Push to remote
• Create PRs

Those are the responsibility of THIS skill (lading-optimize-submit).

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Phase 3: Create Optimization Branch

Create a new branch and add the changes.

# Create descriptive branch name
# Format: opt/<crate>-<technique>
# Examples:
#   opt/payload-cache-prealloc
#   opt/throttle-avoid-clone
#   opt/syslog-buffer-reuse

git checkout -b opt/<crate>-<technique>
git add .

Using the template in .claude/skills/lading-optimize-submit/assets/commit-template.txt, commit the changes:

# Example:
git commit -m "opt: buffer reuse in syslog serialization

Replaced per-iteration format!() with reusable Vec<u8> buffer.

Target: lading_payload/src/syslog.rs::Syslog5424::to_bytes
Technique: buffer-reuse

Micro-benchmarks:
  syslog_100MiB: +42.0% throughput (481 -> 683 MiB/s)

Macro-benchmarks (payloadtool):
  Time: -14.5% (8.3 ms -> 7.1 ms)
  Memory: -35.8% (6.17 MiB -> 3.96 MiB)
  Allocations: -49.3% (67,688 -> 34,331)

Co-Authored-By: Claude Sonnet 4.5 <[email protected]>
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