gspdev-benchmark

Snapshots live in dev/benchmarks/ as JSON files. The workflow is release-centric:

1. At each release, capture a baseline: benchmark.sh release → {version}.release.json
2. During development, capture snapshots: benchmark.sh capture [label]
3. Before PR, compare against release: benchmark.sh compare (auto-selects release baseline)

This measures the cumulative impact of changes heading into the next release.

Read $ARGUMENTS to determine the mode:

Input	Mode
(no args)	Capture + auto-compare against release baseline
capture [label]	Capture with optional label
release	Capture as the release baseline for this version
compare [v1] [v2]	Compare two snapshots (default: release vs latest)
trend	Show trajectory across all snapshots

Step 1: Execute mode

Default mode (no args)

1. Run bash dev/scripts/benchmark.sh capture
2. If a release baseline exists, automatically run benchmark.sh compare
3. Present the comparison table and analysis

This is the most common invocation — "where are we vs the last release?"

Capture mode

Run bash dev/scripts/benchmark.sh capture [label].

After capture, read the JSON from dev/benchmarks/ and present a summary:

• Total weight and red-zone count
• Top 5 heaviest skills with their breakdown
• Rate limit risk (API conversations, double-dispatch count)
• If a release baseline exists, auto-compare and highlight changes

Release mode

Run bash dev/scripts/benchmark.sh release.

This is part of the publish flow — capture the definitive baseline for this version. All future compare calls will diff against this baseline until the next release.

Remind the user: "Add benchmark.sh release to your /gspdev-publish checklist."

Compare mode

Run bash dev/scripts/benchmark.sh compare [v1] [v2].

Default (no args) compares release baseline → latest capture. After the table output, analyze:

• Flag any skill that moved from green/yellow to red
• Flag any skill whose exec_context increased (potential pass-through regression)
• Summarize net pipeline path changes
• Rate limit risk changes
• Highlight the biggest wins and regressions

Trend mode

Run bash dev/scripts/benchmark.sh trend.

After the table, identify:

• Overall trajectory (improving, stable, regressing)
• Largest single-version improvement
• Skills that consistently stay in red zone

Step 2: Suggest next actions

Based on the results, suggest relevant actions:

• If red-zone skills exist: "Consider optimizing {skill} — {specific suggestion}"
• If exec_context is non-zero for agent-spawning skills: "Pass-through exec_context detected in {skill}"
• If rate limit risk increased: "New double-dispatch skill adds API conversation overhead"
• If tests have failures: "Fix test failures before benchmarking"
• If total weight decreased significantly: celebrate the win with specific numbers