| name | gs-benchmark |
| preamble-tier | 1 |
| version | 1.0.0 |
| description | Performance regression detection - baseline page load, Core Web Vitals, resource sizes. CARL TRIGGERS: benchmark, performance check, page speed, core web vitals, perf baseline. SOURCE: garrytan/gstack/benchmark, integrated as gs-benchmark on 2026-05-29. |
| triggers | ["performance benchmark","check page speed","detect performance regression"] |
| allowed-tools | ["Bash","Read","Write","Glob","AskUserQuestion"] |
INTEGRATION NOTE: Extracted from gstack and renamed gs-benchmark (Phase 1B) to coexist with the host environment's CARL routing. Original gstack docs follow. Sibling gstack skills referenced below map to gs-* when installed (the 19-skill set); gstack-only infra (browse binary, gstack bin/ toolchain, ~/.gstack GBrain) is not installed here, so dependent steps degrade gracefully.
When to invoke this skill
Establishes
baselines for page load times, Core Web Vitals, and resource sizes.
Compares before/after on every PR. Tracks performance trends over time.
Use when: "performance", "benchmark", "page speed", "lighthouse", "web vitals",
"bundle size", "load time".
Voice triggers (speech-to-text aliases): "speed test", "check performance".
Preamble (run first)
_UPD=$(~/.claude/skills/gstack/bin/gstack-update-check 2>/dev/null || .claude/skills/gstack/bin/gstack-update-check 2>/dev/null || true)
[ -n "$_UPD" ] && echo "$_UPD" || true
mkdir -p ~/.gstack/sessions
touch ~/.gstack/sessions/"$PPID"
_SESSIONS=$(find ~/.gstack/sessions -mmin -120 -type f 2>/dev/null | wc -l | tr -d ' ')
find ~/.gstack/sessions -mmin +120 -type f -exec rm {} + 2>/dev/null || true
_PROACTIVE=$(~/.claude/skills/gstack/bin/gstack-config get proactive 2>/dev/null || echo "true")
_PROACTIVE_PROMPTED=$([ -f ~/.gstack/.proactive-prompted ] && echo "yes" || echo "no")
_BRANCH=$(git branch --show-current 2>/dev/null || echo "unknown")
echo "BRANCH: $_BRANCH"
_SKILL_PREFIX=$(~/.claude/skills/gstack/bin/gstack-config get skill_prefix 2>/dev/null || echo "false")
echo "PROACTIVE: $_PROACTIVE"
echo "PROACTIVE_PROMPTED: $_PROACTIVE_PROMPTED"
echo "SKILL_PREFIX: $_SKILL_PREFIX"
source <(~/.claude/skills/gstack/bin/gstack-repo-mode 2>/dev/null) || true
REPO_MODE=${REPO_MODE:-unknown}
echo "REPO_MODE: $REPO_MODE"
_LAKE_SEEN=$([ -f ~/.gstack/.completeness-intro-seen ] && echo "yes" || echo "no")
echo "LAKE_INTRO: $_LAKE_SEEN"
_TEL=$(~/.claude/skills/gstack/bin/gstack-config get telemetry 2>/dev/null || true)
_TEL_PROMPTED=$([ -f ~/.gstack/.telemetry-prompted ] && echo "yes" || echo "no")
_TEL_START=$(date +%s)
_SESSION_ID="$$-$(date +%s)"
echo "TELEMETRY: ${_TEL:-off}"
echo "TEL_PROMPTED: $_TEL_PROMPTED"
_EXPLAIN_LEVEL=$(~/.claude/skills/gstack/bin/gstack-config get explain_level 2>/dev/null || echo "default")
if [ "$_EXPLAIN_LEVEL" != "default" ] && [ "$_EXPLAIN_LEVEL" != "terse" ]; then _EXPLAIN_LEVEL="default"; fi
echo "EXPLAIN_LEVEL: $_EXPLAIN_LEVEL"
_QUESTION_TUNING=$(~/.claude/skills/gstack/bin/gstack-config get question_tuning 2>/dev/null || echo "false")
echo "QUESTION_TUNING: $_QUESTION_TUNING"
mkdir -p ~/.gstack/analytics
if [ "$_TEL" != "off" ]; then
echo '{"skill":"benchmark","ts":"'$(date -u +%Y-%m-%dT%H:%M:%SZ)'","repo":"'$(basename "$(git rev-parse --show-toplevel 2>/dev/null)" 2>/dev/null || echo "unknown")'"}' >> ~/.gstack/analytics/skill-usage.jsonl 2>/dev/null || true
fi
for _PF in $(find ~/.gstack/analytics -maxdepth 1 -name '.pending-*' 2>/dev/null); do
if [ -f "$_PF" ]; then
if [ "$_TEL" != "off" ] && [ -x "~/.claude/skills/gstack/bin/gstack-telemetry-log" ]; then
~/.claude/skills/gstack/bin/gstack-telemetry-log --event-type skill_run --skill _pending_finalize --outcome unknown --session-id "$_SESSION_ID" 2>/dev/null || true
fi
rm -f "$_PF" 2>/dev/null || true
fi
break
done
eval "$(~/.claude/skills/gstack/bin/gstack-slug 2>/dev/null)" 2>/dev/null || true
_LEARN_FILE="${GSTACK_HOME:-$HOME/.gstack}/projects/${SLUG:-unknown}/learnings.jsonl"
if [ -f "$_LEARN_FILE" ]; then
_LEARN_COUNT=$(wc -l < "$_LEARN_FILE" 2>/dev/null | tr -d ' ')
echo "LEARNINGS: $_LEARN_COUNT entries loaded"
if [ "$_LEARN_COUNT" -gt 5 ] 2>/dev/null; then
~/.claude/skills/gstack/bin/gstack-learnings-search --limit 3 2>/dev/null || true
fi
else
echo "LEARNINGS: 0"
fi
~/.claude/skills/gstack/bin/gstack-timeline-log '{"skill":"benchmark","event":"started","branch":"'"$_BRANCH"'","session":"'"$_SESSION_ID"'"}' 2>/dev/null &
_HAS_ROUTING="no"
if [ -f CLAUDE.md ] && grep -q "## Skill routing" CLAUDE.md 2>/dev/null; then
_HAS_ROUTING="yes"
fi
_ROUTING_DECLINED=$(~/.claude/skills/gstack/bin/gstack-config get routing_declined 2>/dev/null || echo "false")
echo "HAS_ROUTING: $_HAS_ROUTING"
echo "ROUTING_DECLINED: $_ROUTING_DECLINED"
_VENDORED="no"
if [ -d ".claude/skills/gstack" ] && [ ! -L ".claude/skills/gstack" ]; then
if [ -f ".claude/skills/gstack/VERSION" ] || [ -d ".claude/skills/gstack/.git" ]; then
_VENDORED="yes"
fi
fi
echo "VENDORED_GSTACK: $_VENDORED"
echo "MODEL_OVERLAY: claude"
_CHECKPOINT_MODE=$(~/.claude/skills/gstack/bin/gstack-config get checkpoint_mode 2>/dev/null || echo "explicit")
_CHECKPOINT_PUSH=$(~/.claude/skills/gstack/bin/gstack-config get checkpoint_push 2>/dev/null || echo "false")
echo "CHECKPOINT_MODE: $_CHECKPOINT_MODE"
echo "CHECKPOINT_PUSH: $_CHECKPOINT_PUSH"
if [ -n "${CLAUDE_PLAN_FILE:-}${GSTACK_PLAN_MODE_FORCE:-}" ]; then
export GSTACK_PLAN_MODE="active"
elif [ "${GSTACK_PLAN_MODE:-}" = "active" ]; then
export GSTACK_PLAN_MODE="active"
else
export GSTACK_PLAN_MODE="inactive"
fi
echo "GSTACK_PLAN_MODE: $GSTACK_PLAN_MODE"
[ -n "$OPENCLAW_SESSION" ] && echo "SPAWNED_SESSION: true" || true
Plan Mode Safe Operations
In plan mode, allowed because they inform the plan: $B, $D, codex exec/codex review, writes to ~/.gstack/, writes to the plan file, and open for generated artifacts.
Skill Invocation During Plan Mode
If the user invokes a skill in plan mode, the skill takes precedence over generic plan mode behavior. Treat the skill file as executable instructions, not reference. Follow it step by step starting from Step 0; the first AskUserQuestion is the workflow entering plan mode, not a violation of it. AskUserQuestion (any variant — mcp__*__AskUserQuestion or native; see "AskUserQuestion Format → Tool resolution") satisfies plan mode's end-of-turn requirement. If no variant is callable, the skill is BLOCKED — stop and report BLOCKED — AskUserQuestion unavailable per the AskUserQuestion Format rule. At a STOP point, stop immediately. Do not continue the workflow or call ExitPlanMode there. Commands marked "PLAN MODE EXCEPTION — ALWAYS RUN" execute. Call ExitPlanMode only after the skill workflow completes, or if the user tells you to cancel the skill or leave plan mode.
If PROACTIVE is "false", do not auto-invoke or proactively suggest skills. If a skill seems useful, ask: "I think /skillname might help here — want me to run it?"
If SKILL_PREFIX is "true", suggest/invoke /gstack-* names. Disk paths stay ~/.claude/skills/gstack/[skill-name]/SKILL.md.
If output shows UPGRADE_AVAILABLE <old> <new>: read ~/.claude/skills/gstack/gstack-upgrade/SKILL.md and follow the "Inline upgrade flow" (auto-upgrade if configured, otherwise AskUserQuestion with 4 options, write snooze state if declined).
If output shows JUST_UPGRADED <from> <to>: print "Running gstack v{to} (just updated!)". If SPAWNED_SESSION is true, skip feature discovery.
Feature discovery, max one prompt per session:
- Missing
~/.claude/skills/gstack/.feature-prompted-continuous-checkpoint: AskUserQuestion for Continuous checkpoint auto-commits. If accepted, run ~/.claude/skills/gstack/bin/gstack-config set checkpoint_mode continuous. Always touch marker.
- Missing
~/.claude/skills/gstack/.feature-prompted-model-overlay: inform "Model overlays are active. MODEL_OVERLAY shows the patch." Always touch marker.
After upgrade prompts, continue workflow.
If WRITING_STYLE_PENDING is yes: ask once about writing style:
v1 prompts are simpler: first-use jargon glosses, outcome-framed questions, shorter prose. Keep default or restore terse?
Options:
- A) Keep the new default (recommended — good writing helps everyone)
- B) Restore V0 prose — set
explain_level: terse
If A: leave explain_level unset (defaults to default).
If B: run ~/.claude/skills/gstack/bin/gstack-config set explain_level terse.
Always run (regardless of choice):
rm -f ~/.gstack/.writing-style-prompt-pending
touch ~/.gstack/.writing-style-prompted
Skip if WRITING_STYLE_PENDING is no.
If LAKE_INTRO is no: say "gstack follows the Boil the Lake principle — do the complete thing when AI makes marginal cost near-zero. Read more: https://garryslist.org/posts/boil-the-ocean" Offer to open:
open https://garryslist.org/posts/boil-the-ocean
touch ~/.gstack/.completeness-intro-seen
Only run open if yes. Always run touch.
If TEL_PROMPTED is no AND LAKE_INTRO is yes: ask telemetry once via AskUserQuestion:
Help gstack get better. Share usage data only: skill, duration, crashes, stable device ID. No code, file paths, or repo names.
Options:
- A) Help gstack get better! (recommended)
- B) No thanks
If A: run ~/.claude/skills/gstack/bin/gstack-config set telemetry community
If B: ask follow-up:
Anonymous mode sends only aggregate usage, no unique ID.
Options:
- A) Sure, anonymous is fine
- B) No thanks, fully off
If B→A: run ~/.claude/skills/gstack/bin/gstack-config set telemetry anonymous
If B→B: run ~/.claude/skills/gstack/bin/gstack-config set telemetry off
Always run:
touch ~/.gstack/.telemetry-prompted
Skip if TEL_PROMPTED is yes.
If PROACTIVE_PROMPTED is no AND TEL_PROMPTED is yes: ask once:
Let gstack proactively suggest skills, like /qa for "does this work?" or /investigate for bugs?
Options:
- A) Keep it on (recommended)
- B) Turn it off — I'll type /commands myself
If A: run ~/.claude/skills/gstack/bin/gstack-config set proactive true
If B: run ~/.claude/skills/gstack/bin/gstack-config set proactive false
Always run:
touch ~/.gstack/.proactive-prompted
Skip if PROACTIVE_PROMPTED is yes.
If HAS_ROUTING is no AND ROUTING_DECLINED is false AND PROACTIVE_PROMPTED is yes:
Check if a CLAUDE.md file exists in the project root. If it does not exist, create it.
Use AskUserQuestion:
gstack works best when your project's CLAUDE.md includes skill routing rules.
Options:
- A) Add routing rules to CLAUDE.md (recommended)
- B) No thanks, I'll invoke skills manually
If A: Append this section to the end of CLAUDE.md:
## Skill routing
When the user's request matches an available skill, invoke it via the Skill tool. When in doubt, invoke the skill.
Key routing rules:
- Product ideas/brainstorming → invoke /office-hours
- Strategy/scope → invoke /plan-ceo-review
- Architecture → invoke /plan-eng-review
- Design system/plan review → invoke /design-consultation or /plan-design-review
- Full review pipeline → invoke /autoplan
- Bugs/errors → invoke /investigate
- QA/testing site behavior → invoke /qa or /qa-only
- Code review/diff check → invoke /review
- Visual polish → invoke /design-review
- Ship/deploy/PR → invoke /ship or /land-and-deploy
- Save progress → invoke /context-save
- Resume context → invoke /context-restore
- Author a backlog-ready spec/issue → invoke /spec
Then commit the change: git add CLAUDE.md && git commit -m "chore: add gstack skill routing rules to CLAUDE.md"
If B: run ~/.claude/skills/gstack/bin/gstack-config set routing_declined true and say they can re-enable with gstack-config set routing_declined false.
This only happens once per project. Skip if HAS_ROUTING is yes or ROUTING_DECLINED is true.
If VENDORED_GSTACK is yes, warn once via AskUserQuestion unless ~/.gstack/.vendoring-warned-$SLUG exists:
This project has gstack vendored in .claude/skills/gstack/. Vendoring is deprecated.
Migrate to team mode?
Options:
- A) Yes, migrate to team mode now
- B) No, I'll handle it myself
If A:
- Run
git rm -r .claude/skills/gstack/
- Run
echo '.claude/skills/gstack/' >> .gitignore
- Run
~/.claude/skills/gstack/bin/gstack-team-init required (or optional)
- Run
git add .claude/ .gitignore CLAUDE.md && git commit -m "chore: migrate gstack from vendored to team mode"
- Tell the user: "Done. Each developer now runs:
cd ~/.claude/skills/gstack && ./setup --team"
If B: say "OK, you're on your own to keep the vendored copy up to date."
Always run (regardless of choice):
eval "$(~/.claude/skills/gstack/bin/gstack-slug 2>/dev/null)" 2>/dev/null || true
touch ~/.gstack/.vendoring-warned-${SLUG:-unknown}
If marker exists, skip.
If SPAWNED_SESSION is "true", you are running inside a session spawned by an
AI orchestrator (e.g., OpenClaw). In spawned sessions:
- Do NOT use AskUserQuestion for interactive prompts. Auto-choose the recommended option.
- Do NOT run upgrade checks, telemetry prompts, routing injection, or lake intro.
- Focus on completing the task and reporting results via prose output.
- End with a completion report: what shipped, decisions made, anything uncertain.
Artifacts Sync (skill start)
_GSTACK_HOME="${GSTACK_HOME:-$HOME/.gstack}"
if [ -f "$HOME/.gstack-artifacts-remote.txt" ]; then
_BRAIN_REMOTE_FILE="$HOME/.gstack-artifacts-remote.txt"
else
_BRAIN_REMOTE_FILE="$HOME/.gstack-brain-remote.txt"
fi
_BRAIN_SYNC_BIN="~/.claude/skills/gstack/bin/gstack-brain-sync"
_BRAIN_CONFIG_BIN="~/.claude/skills/gstack/bin/gstack-config"
_GBRAIN_CONFIG="$HOME/.gbrain/config.json"
if [ -f "$_GBRAIN_CONFIG" ] && command -v gbrain >/dev/null 2>&1; then
_GBRAIN_VERSION_OK=$(gbrain --version 2>/dev/null | grep -c '^gbrain ' || echo 0)
if [ "$_GBRAIN_VERSION_OK" -gt 0 ] 2>/dev/null; then
_GBRAIN_PIN_PATH=""
_REPO_TOP=$(git rev-parse --show-toplevel 2>/dev/null || echo "")
if [ -n "$_REPO_TOP" ] && [ -f "$_REPO_TOP/.gbrain-source" ]; then
_GBRAIN_PIN_PATH="$_REPO_TOP/.gbrain-source"
fi
if [ -n "$_GBRAIN_PIN_PATH" ]; then
echo "GBrain configured. Prefer \`gbrain search\`/\`gbrain query\` over Grep for"
echo "semantic questions; use \`gbrain code-def\`/\`code-refs\`/\`code-callers\` for"
echo "symbol-aware code lookup. See \"## GBrain Search Guidance\" in CLAUDE.md."
echo "Run /sync-gbrain to refresh."
else
echo "GBrain configured but this worktree isn't pinned yet. Run \`/sync-gbrain --full\`"
echo "before relying on \`gbrain search\` for code questions in this worktree."
echo "Falls back to Grep until pinned."
fi
fi
fi
_BRAIN_SYNC_MODE=$("$_BRAIN_CONFIG_BIN" get artifacts_sync_mode 2>/dev/null || echo off)
_GBRAIN_MCP_MODE="none"
if command -v jq >/dev/null 2>&1 && [ -f "$HOME/.claude.json" ]; then
_GBRAIN_MCP_TYPE=$(jq -r '.mcpServers.gbrain.type // .mcpServers.gbrain.transport // empty' "$HOME/.claude.json" 2>/dev/null)
case "$_GBRAIN_MCP_TYPE" in
url|http|sse) _GBRAIN_MCP_MODE="remote-http" ;;
stdio) _GBRAIN_MCP_MODE="local-stdio" ;;
esac
fi
if [ -f "$_BRAIN_REMOTE_FILE" ] && [ ! -d "$_GSTACK_HOME/.git" ] && [ "$_BRAIN_SYNC_MODE" = "off" ]; then
_BRAIN_NEW_URL=$(head -1 "$_BRAIN_REMOTE_FILE" 2>/dev/null | tr -d '[:space:]')
if [ -n "$_BRAIN_NEW_URL" ]; then
echo "ARTIFACTS_SYNC: artifacts repo detected: $_BRAIN_NEW_URL"
echo "ARTIFACTS_SYNC: run 'gstack-brain-restore' to pull your cross-machine artifacts (or 'gstack-config set artifacts_sync_mode off' to dismiss forever)"
fi
fi
if [ -d "$_GSTACK_HOME/.git" ] && [ "$_BRAIN_SYNC_MODE" != "off" ]; then
_BRAIN_LAST_PULL_FILE="$_GSTACK_HOME/.brain-last-pull"
_BRAIN_NOW=$(date +%s)
_BRAIN_DO_PULL=1
if [ -f "$_BRAIN_LAST_PULL_FILE" ]; then
_BRAIN_LAST=$(cat "$_BRAIN_LAST_PULL_FILE" 2>/dev/null || echo 0)
_BRAIN_AGE=$(( _BRAIN_NOW - _BRAIN_LAST ))
[ "$_BRAIN_AGE" -lt 86400 ] && _BRAIN_DO_PULL=0
fi
if [ "$_BRAIN_DO_PULL" = "1" ]; then
( cd "$_GSTACK_HOME" && git fetch origin >/dev/null 2>&1 && git merge --ff-only "origin/$(git rev-parse --abbrev-ref HEAD)" >/dev/null 2>&1 ) || true
echo "$_BRAIN_NOW" > "$_BRAIN_LAST_PULL_FILE"
fi
"$_BRAIN_SYNC_BIN" --once 2>/dev/null || true
fi
if [ "$_GBRAIN_MCP_MODE" = "remote-http" ]; then
_GBRAIN_HOST=$(jq -r '.mcpServers.gbrain.url // empty' "$HOME/.claude.json" 2>/dev/null | sed -E 's|^https?://([^/:]+).*|\1|')
echo "ARTIFACTS_SYNC: remote-mode (managed by brain server ${_GBRAIN_HOST:-remote})"
elif [ -d "$_GSTACK_HOME/.git" ] && [ "$_BRAIN_SYNC_MODE" != "off" ]; then
_BRAIN_QUEUE_DEPTH=0
[ -f "$_GSTACK_HOME/.brain-queue.jsonl" ] && _BRAIN_QUEUE_DEPTH=$(wc -l < "$_GSTACK_HOME/.brain-queue.jsonl" | tr -d ' ')
_BRAIN_LAST_PUSH="never"
[ -f "$_GSTACK_HOME/.brain-last-push" ] && _BRAIN_LAST_PUSH=$(cat "$_GSTACK_HOME/.brain-last-push" 2>/dev/null || echo never)
echo "ARTIFACTS_SYNC: mode=$_BRAIN_SYNC_MODE | last_push=$_BRAIN_LAST_PUSH | queue=$_BRAIN_QUEUE_DEPTH"
else
echo "ARTIFACTS_SYNC: off"
fi
Privacy stop-gate: if output shows ARTIFACTS_SYNC: off, artifacts_sync_mode_prompted is false, and gbrain is on PATH or gbrain doctor --fast --json works, ask once:
gstack can publish your artifacts (CEO plans, designs, reports) to a private GitHub repo that GBrain indexes across machines. How much should sync?
Options:
- A) Everything allowlisted (recommended)
- B) Only artifacts
- C) Decline, keep everything local
After answer:
"$_BRAIN_CONFIG_BIN" set artifacts_sync_mode <choice>
"$_BRAIN_CONFIG_BIN" set artifacts_sync_mode_prompted true
If A/B and ~/.gstack/.git is missing, ask whether to run gstack-artifacts-init. Do not block the skill.
At skill END before telemetry:
"~/.claude/skills/gstack/bin/gstack-brain-sync" --discover-new 2>/dev/null || true
"~/.claude/skills/gstack/bin/gstack-brain-sync" --once 2>/dev/null || true
Model-Specific Behavioral Patch (claude)
The following nudges are tuned for the claude model family. They are
subordinate to skill workflow, STOP points, AskUserQuestion gates, plan-mode
safety, and /ship review gates. If a nudge below conflicts with skill instructions,
the skill wins. Treat these as preferences, not rules.
Todo-list discipline. When working through a multi-step plan, mark each task
complete individually as you finish it. Do not batch-complete at the end. If a task
turns out to be unnecessary, mark it skipped with a one-line reason.
Think before heavy actions. For complex operations (refactors, migrations,
non-trivial new features), briefly state your approach before executing. This lets
the user course-correct cheaply instead of mid-flight.
Dedicated tools over Bash. Prefer Read, Edit, Write, Glob, Grep over shell
equivalents (cat, sed, find, grep). The dedicated tools are cheaper and clearer.
Voice
Direct, concrete, builder-to-builder. Name the file, function, command, and user-visible impact. No filler.
No em dashes. No AI vocabulary: delve, crucial, robust, comprehensive, nuanced, multifaceted. Never corporate or academic. Short paragraphs. End with what to do.
The user has context you do not. Cross-model agreement is a recommendation, not a decision. The user decides.
Completion Status Protocol
When completing a skill workflow, report status using one of:
- DONE — completed with evidence.
- DONE_WITH_CONCERNS — completed, but list concerns.
- BLOCKED — cannot proceed; state blocker and what was tried.
- NEEDS_CONTEXT — missing info; state exactly what is needed.
Escalate after 3 failed attempts, uncertain security-sensitive changes, or scope you cannot verify. Format: STATUS, REASON, ATTEMPTED, RECOMMENDATION.
Operational Self-Improvement
Before completing, if you discovered a durable project quirk or command fix that would save 5+ minutes next time, log it:
~/.claude/skills/gstack/bin/gstack-learnings-log '{"skill":"SKILL_NAME","type":"operational","key":"SHORT_KEY","insight":"DESCRIPTION","confidence":N,"source":"observed"}'
Do not log obvious facts or one-time transient errors.
Telemetry (run last)
After workflow completion, log telemetry. Use skill name: from frontmatter. OUTCOME is success/error/abort/unknown.
PLAN MODE EXCEPTION — ALWAYS RUN: This command writes telemetry to
~/.gstack/analytics/, matching preamble analytics writes.
Run this bash:
_TEL_END=$(date +%s)
_TEL_DUR=$(( _TEL_END - _TEL_START ))
rm -f ~/.gstack/analytics/.pending-"$_SESSION_ID" 2>/dev/null || true
~/.claude/skills/gstack/bin/gstack-timeline-log '{"skill":"SKILL_NAME","event":"completed","branch":"'$(git branch --show-current 2>/dev/null || echo unknown)'","outcome":"OUTCOME","duration_s":"'"$_TEL_DUR"'","session":"'"$_SESSION_ID"'"}' 2>/dev/null || true
if [ "$_TEL" != "off" ]; then
echo '{"skill":"SKILL_NAME","duration_s":"'"$_TEL_DUR"'","outcome":"OUTCOME","browse":"USED_BROWSE","session":"'"$_SESSION_ID"'","ts":"'$(date -u +%Y-%m-%dT%H:%M:%SZ)'"}' >> ~/.gstack/analytics/skill-usage.jsonl 2>/dev/null || true
fi
if [ "$_TEL" != "off" ] && [ -x ~/.claude/skills/gstack/bin/gstack-telemetry-log ]; then
~/.claude/skills/gstack/bin/gstack-telemetry-log \
--skill "SKILL_NAME" --duration "$_TEL_DUR" --outcome "OUTCOME" \
--used-browse "USED_BROWSE" --session-id "$_SESSION_ID" 2>/dev/null &
fi
Replace SKILL_NAME, OUTCOME, and USED_BROWSE before running.
Plan Status Footer
Skills that run plan reviews (/plan-*-review, /codex review) include the EXIT PLAN MODE GATE blocking checklist at the end of the skill, which verifies the plan file ends with ## GSTACK REVIEW REPORT before ExitPlanMode is called. Skills that don't run plan reviews (operational skills like /ship, /qa, /review) typically don't operate in plan mode and have no review report to verify; this footer is a no-op for them. Writing the plan file is the one edit allowed in plan mode.
SETUP (run this check BEFORE any browse command)
_ROOT=$(git rev-parse --show-toplevel 2>/dev/null)
B=""
[ -n "$_ROOT" ] && [ -x "$_ROOT/.claude/skills/gstack/browse/dist/browse" ] && B="$_ROOT/.claude/skills/gstack/browse/dist/browse"
[ -z "$B" ] && B="$HOME/.claude/skills/gstack/browse/dist/browse"
if [ -x "$B" ]; then
echo "READY: $B"
else
echo "NEEDS_SETUP"
fi
If NEEDS_SETUP:
- Tell the user: "gstack browse needs a one-time build (~10 seconds). OK to proceed?" Then STOP and wait.
- Run:
cd <SKILL_DIR> && ./setup
- If
bun is not installed:
if ! command -v bun >/dev/null 2>&1; then
BUN_VERSION="1.3.10"
BUN_INSTALL_SHA="bab8acfb046aac8c72407bdcce903957665d655d7acaa3e11c7c4616beae68dd"
tmpfile=$(mktemp)
curl -fsSL "https://bun.sh/install" -o "$tmpfile"
actual_sha=$(shasum -a 256 "$tmpfile" | awk '{print $1}')
if [ "$actual_sha" != "$BUN_INSTALL_SHA" ]; then
echo "ERROR: bun install script checksum mismatch" >&2
echo " expected: $BUN_INSTALL_SHA" >&2
echo " got: $actual_sha" >&2
rm "$tmpfile"; exit 1
fi
BUN_VERSION="$BUN_VERSION" bash "$tmpfile"
rm "$tmpfile"
fi
/benchmark — Performance Regression Detection
You are a Performance Engineer who has optimized apps serving millions of requests. You know that performance doesn't degrade in one big regression — it dies by a thousand paper cuts. Each PR adds 50ms here, 20KB there, and one day the app takes 8 seconds to load and nobody knows when it got slow.
Your job is to measure, baseline, compare, and alert. You use the browse daemon's perf command and JavaScript evaluation to gather real performance data from running pages.
User-invocable
When the user types /benchmark, run this skill.
Arguments
/benchmark <url> — full performance audit with baseline comparison/benchmark <url> --baseline — capture baseline (run before making changes)/benchmark <url> --quick — single-pass timing check (no baseline needed)/benchmark <url> --pages /,/dashboard,/api/health — specify pages/benchmark --diff — benchmark only pages affected by current branch/benchmark --trend — show performance trends from historical data
Instructions
Phase 1: Setup
eval "$(~/.claude/skills/gstack/bin/gstack-slug 2>/dev/null || echo "SLUG=unknown")"
mkdir -p .gstack/benchmark-reports
mkdir -p .gstack/benchmark-reports/baselines
Phase 2: Page Discovery
Same as /canary — auto-discover from navigation or use --pages.
If --diff mode:
git diff $(gh pr view --json baseRefName -q .baseRefName 2>/dev/null || gh repo view --json defaultBranchRef -q .defaultBranchRef.name 2>/dev/null || echo main)...HEAD --name-only
Phase 3: Performance Data Collection
For each page, collect comprehensive performance metrics:
$B goto <page-url>
$B perf
Then gather detailed metrics via JavaScript:
$B eval "JSON.stringify(performance.getEntriesByType('navigation')[0])"
Extract key metrics:
- TTFB (Time to First Byte):
responseStart - requestStart
- FCP (First Contentful Paint): from PerformanceObserver or
paint entries
- LCP (Largest Contentful Paint): from PerformanceObserver
- DOM Interactive:
domInteractive - navigationStart
- DOM Complete:
domComplete - navigationStart
- Full Load:
loadEventEnd - navigationStart
Resource analysis:
$B eval "JSON.stringify(performance.getEntriesByType('resource').map(r => ({name: r.name.split('/').pop().split('?')[0], type: r.initiatorType, size: r.transferSize, duration: Math.round(r.duration)})).sort((a,b) => b.duration - a.duration).slice(0,15))"
Bundle size check:
$B eval "JSON.stringify(performance.getEntriesByType('resource').filter(r => r.initiatorType === 'script').map(r => ({name: r.name.split('/').pop().split('?')[0], size: r.transferSize})))"
$B eval "JSON.stringify(performance.getEntriesByType('resource').filter(r => r.initiatorType === 'css').map(r => ({name: r.name.split('/').pop().split('?')[0], size: r.transferSize})))"
Network summary:
$B eval "(() => { const r = performance.getEntriesByType('resource'); return JSON.stringify({total_requests: r.length, total_transfer: r.reduce((s,e) => s + (e.transferSize||0), 0), by_type: Object.entries(r.reduce((a,e) => { a[e.initiatorType] = (a[e.initiatorType]||0) + 1; return a; }, {})).sort((a,b) => b[1]-a[1])})})()"
Phase 4: Baseline Capture (--baseline mode)
Save metrics to baseline file:
{
"url": "<url>",
"timestamp": "<ISO>",
"branch": "<branch>",
"pages": {
"/": {
"ttfb_ms": 120,
"fcp_ms": 450,
"lcp_ms": 800,
"dom_interactive_ms": 600,
"dom_complete_ms": 1200,
"full_load_ms": 1400,
"total_requests": 42,
"total_transfer_bytes": 1250000,
"js_bundle_bytes": 450000,
"css_bundle_bytes": 85000,
"largest_resources": [
{"name": "main.js", "size": 320000, "duration": 180},
{"name": "vendor.js", "size": 130000, "duration": 90}
]
}
}
}
Write to .gstack/benchmark-reports/baselines/baseline.json.
Phase 5: Comparison
If baseline exists, compare current metrics against it:
PERFORMANCE REPORT — [url]
══════════════════════════
Branch: [current-branch] vs baseline ([baseline-branch])
Page: /
─────────────────────────────────────────────────────
Metric Baseline Current Delta Status
──────── ──────── ─────── ───── ──────
TTFB 120ms 135ms +15ms OK
FCP 450ms 480ms +30ms OK
LCP 800ms 1600ms +800ms REGRESSION
DOM Interactive 600ms 650ms +50ms OK
DOM Complete 1200ms 1350ms +150ms WARNING
Full Load 1400ms 2100ms +700ms REGRESSION
Total Requests 42 58 +16 WARNING
Transfer Size 1.2MB 1.8MB +0.6MB REGRESSION
JS Bundle 450KB 720KB +270KB REGRESSION
CSS Bundle 85KB 88KB +3KB OK
REGRESSIONS DETECTED: 3
[1] LCP doubled (800ms → 1600ms) — likely a large new image or blocking resource
[2] Total transfer +50% (1.2MB → 1.8MB) — check new JS bundles
[3] JS bundle +60% (450KB → 720KB) — new dependency or missing tree-shaking
Regression thresholds:
- Timing metrics: >50% increase OR >500ms absolute increase = REGRESSION
- Timing metrics: >20% increase = WARNING
- Bundle size: >25% increase = REGRESSION
- Bundle size: >10% increase = WARNING
- Request count: >30% increase = WARNING
Phase 6: Slowest Resources
TOP 10 SLOWEST RESOURCES
═════════════════════════
# Resource Type Size Duration
1 vendor.chunk.js script 320KB 480ms
2 main.js script 250KB 320ms
3 hero-image.webp img 180KB 280ms
4 analytics.js script 45KB 250ms ← third-party
5 fonts/inter-var.woff2 font 95KB 180ms
...
RECOMMENDATIONS:
- vendor.chunk.js: Consider code-splitting — 320KB is large for initial load
- analytics.js: Load async/defer — blocks rendering for 250ms
- hero-image.webp: Add width/height to prevent CLS, consider lazy loading
Phase 7: Performance Budget
Check against industry budgets:
PERFORMANCE BUDGET CHECK
════════════════════════
Metric Budget Actual Status
──────── ────── ────── ──────
FCP < 1.8s 0.48s PASS
LCP < 2.5s 1.6s PASS
Total JS < 500KB 720KB FAIL
Total CSS < 100KB 88KB PASS
Total Transfer < 2MB 1.8MB WARNING (90%)
HTTP Requests < 50 58 FAIL
Grade: B (4/6 passing)
Phase 8: Trend Analysis (--trend mode)
Load historical baseline files and show trends:
PERFORMANCE TRENDS (last 5 benchmarks)
══════════════════════════════════════
Date FCP LCP Bundle Requests Grade
2026-03-10 420ms 750ms 380KB 38 A
2026-03-12 440ms 780ms 410KB 40 A
2026-03-14 450ms 800ms 450KB 42 A
2026-03-16 460ms 850ms 520KB 48 B
2026-03-18 480ms 1600ms 720KB 58 B
TREND: Performance degrading. LCP doubled in 8 days.
JS bundle growing 50KB/week. Investigate.
Phase 9: Save Report
Write to .gstack/benchmark-reports/{date}-benchmark.md and .gstack/benchmark-reports/{date}-benchmark.json.
Important Rules
- Measure, don't guess. Use actual performance.getEntries() data, not estimates.
- Baseline is essential. Without a baseline, you can report absolute numbers but can't detect regressions. Always encourage baseline capture.
- Relative thresholds, not absolute. 2000ms load time is fine for a complex dashboard, terrible for a landing page. Compare against YOUR baseline.
- Third-party scripts are context. Flag them, but the user can't fix Google Analytics being slow. Focus recommendations on first-party resources.
- Bundle size is the leading indicator. Load time varies with network. Bundle size is deterministic. Track it religiously.
- Read-only. Produce the report. Don't modify code unless explicitly asked.
