make-pdf
Turn any markdown file into a publication-quality PDF. Proper 1in margins, intelligent page breaks, page numbers, cover pages, running headers, curly quotes and em dashes, clickable TOC, diagonal DRAFT watermark. Not a draft artifact — a finished artifact. Use when asked to "make a PDF", "export to PDF", "turn this markdown into a PDF", or "generate a document". (gstack) Voice triggers (speech-to-text aliases): "make this a pdf", "make it a pdf", "export to pdf", "turn this into a pdf", "turn this markdown into a pdf", "generate a pdf", "make a pdf from", "pdf this markdown".
What this skill does
<!-- AUTO-GENERATED from SKILL.md.tmpl — do not edit directly -->
<!-- Regenerate: bun run gen:skill-docs -->
## Preamble (run first)
```bash
_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: $_TEL_PROMPTED"
# Writing style verbosity (V1: default = ELI10, terse = tighter V0 prose.
# Read on every skill run so terse mode takes effect without a restart.)
_EXPLAIN_LEVEL=$(~/.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: $_EXPLAIN_LEVEL"
# Question tuning (see /plan-tune). Observational only in V1.
_QUESTION_TUNING=$(~/.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":"make-pdf","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
# zsh-compatible: use find instead of glob to avoid NOMATCH error
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 "$_PF" 2>/dev/null || true
fi
break
done
# Learnings count
eval "$(~/.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
# Session timeline: record skill start (local-only, never sent anywhere)
~/.claude/skills/gstack/bin/gstack-timeline-log '{"skill":"make-pdf","event":"started","branch":"'"$_BRANCH"'","session":"'"$_SESSION_ID"'"}' 2>/dev/null &
# Check if CLAUDE.md has routing rules
_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"
# Vendoring deprecation: detect if CWD has a vendored gstack copy
_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: $_VENDORED"
echo "MODEL_OVERLAY: claude"
# Checkpoint mode (explicit = no auto-commit, continuous = WIP commits as you go)
_CHECKPOINT_MODE=$(~/.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: $_CHECKPOINT_PUSH"
# Detect spawned session (OpenClaw or other orchestrator)
[ -n "$OPENCLAW_SESSION" ] && echo "SPAWNED_SESSION: true" || true
```
If `PROACTIVE` is `"false"`, do not proactively suggest gstack skills AND do not
auto-invoke skills based on conversation context. Only run skills the user explicitly
types (e.g., /qa, /ship). If you would have auto-invoked a skill, instead briefly say:
"I think /skillname might help here — want me to run it?" and wait for confirmation.
The user opted out of proactive behavior.
If `SKILL_PREFIX` is `"true"`, the user has namespaced skill names. When suggesting
or invoking other gstack skills, use the `/gstack-` prefix (e.g., `/gstack-qa` instead
of `/qa`, `/gstack-ship` instead of `/ship`). Disk paths are unaffected — always use
`~/.claude/skills/gstack/[skill-name]/SKILL.md` for reading skill files.
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>` AND `SPAWNED_SESSION` is NOT set: tell
the user "Running gstack v{to} (just updated!)" and then check for new features to
surface. For each per-feature marker below, if the marker file is missing AND the
feature is plausibly useful for this user, use AskUserQuestion to let them try it.
Fire once per feature per user, NOT once per upgrade.
**In spawned sessions (`SPAWNED_SESSION` = "true"): SKIP feature discovery entirely.**
Just print "Running gstack v{to}" and continue. Orchestrators do not want interactive
prompts from sub-sessions.
**Feature discovery markers and prompts** (one at a time, max one per session):
1. `~/.claude/skills/gstack/.feature-prompted-continuous-checkpoint` →
Prompt: "Continuous checkpoint auto-commits your work as you go with `WIP:` prefix
so you never lose progress to a crash. Local-only by default — doesn't push
anywhere unless you turn that on. Want to try it?"
Options: A) Enable continuous mode, B) Show me first (print the section from
the preamble Continuous Checkpoint Mode), C) Skip.
If A: run `~/.claude/skills/gstack/bin/gstack-config set checkpoint_mode continuous`.
Always: `touch ~/.claude/skills/gstack/.feature-prompted-continuous-checkpoint`
2. `~/.claude/skills/gstack/.feature-prompted-model-overlay` →
Inform only (no prompt): "Model overlays are active. `MODEL_OVERLAY: {model}`
shown in the preamble output tells you which behavioral patch is applied.
Override with `--model` when regenerating skills (e.g., `bun run gen:skill-docs
--model gpt-5.4`). Default is claude."
Always: `touch ~/.claude/skills/gstack/.feature-prompted-model-overlay`
After handling JUST_UPGRADED (prompts done or skipped), continue with the skill
workflow.
If `WRITING_STYLE_PENDING` is `yes`: You're on the first skill run after upgrading
to gstack v1. Ask the user once about the new default writing style. Use AskUserQuestion:
> v1 prompts = simpler. Technical terms get a one-sentence gloss on first use,
> questions are framed in outcome terms, sentences are shorter.
>
> Keep the new default, Related in Image & Video
watch
IncludedWatch a video (URL or local path). Downloads with yt-dlp, extracts auto-scaled frames with ffmpeg, pulls the transcript from captions (or Whisper API fallback), and hands the result to Claude so it can answer questions about what's in the video.
physical-ai-defect-image-generation
IncludedUse when the user wants to orchestrate defect image generation, run associated setup, or handle outputs on OSMO. The Day 0 path handles cold-start with USD-to-ROI, image-edit augmentation, and AnomalyGen to create initial PCBA datasets. The Day 1 path performs inference and labeling on real images. This skill helps with first-time asset setup, creation of finetuning checkpoints, and configuring deployment. Trigger keywords: defect image generation, dig workflow, dig pipeline, defect image detection workflow, aoi pipeline, aoi anomalygen, usd2roi anomalygen, day 0 pcba, day 1 pcba, day 1 real-photo alignment, day 1 manual roi, metal surface anomaly, glass defect, anomalygen finetune, setup_pcb, setup_metal, setup_glass, setup_pretrained, dig setup, dig datasets, dig pretrained checkpoint, dig image-edit endpoint.
accelint-react-best-practices
IncludedReact performance optimization and best practices. ALWAYS use this skill when working with any React code - writing components, hooks, JSX; refactoring; optimizing re-renders, memoization, state management; reviewing for performance; fixing hydration mismatches; debugging infinite re-renders, stale closures, input focus loss, animations restarting; preventing remounting; implementing transitions, lazy initialization, effect dependencies. Even simple React tasks benefit from these patterns. Covers React 19+ (useEffectEvent, Activity, ref props). Triggers - useEffect, useState, useMemo, useCallback, memo, inline components, nested components, components inside components, re-render, performance, hydration, SSR, Next.js, useDeferredValue, combined hooks.
elevenlabs-agents
IncludedBuild conversational AI voice agents with ElevenLabs Platform using React, JavaScript, React Native, or Swift SDKs. Configure agents, tools (client/server/MCP), RAG knowledge bases, multi-voice, and Scribe real-time STT. Use when: building voice chat interfaces, implementing AI phone agents with Twilio, configuring agent workflows or tools, adding RAG knowledge bases, testing with CLI "agents as code", or troubleshooting deprecated @11labs packages, Android audio cutoff, CSP violations, dynamic variables, or WebRTC config. Keywords: ElevenLabs Agents, ElevenLabs voice agents, AI voice agents, conversational AI, @elevenlabs/react, @elevenlabs/client, @elevenlabs/react-native, @elevenlabs/elevenlabs-js, @elevenlabs/agents-cli, elevenlabs SDK, voice AI, TTS, text-to-speech, ASR, speech recognition, turn-taking model, WebRTC voice, WebSocket voice, ElevenLabs conversation, agent system prompt, agent tools, agent knowledge base, RAG voice agents, multi-voice agents, pronunciation dictionary, voice speed control, elevenlabs scribe, @11labs deprecated, Android audio cutoff, CSP violation elevenlabs, dynamic variables elevenlabs, case-sensitive tool names, webhook authentication
humanizer
IncludedHumanize AI-generated text by detecting and removing patterns typical of LLM output. Rewrites text to sound natural, specific, and human. Uses 28 pattern detectors, 560+ AI vocabulary terms across 3 tiers, and statistical analysis (burstiness, type-token ratio, readability) for comprehensive detection. Use when asked to humanize text, de-AI writing, make content sound more natural/human, review writing for AI patterns, score text for AI detection, or improve AI-generated drafts. Covers content, language, style, communication, and filler categories.
generating-mermaid-diagrams
IncludedSalesforce architecture diagrams using Mermaid with ASCII fallback. Use this skill when generating text-based diagrams for Salesforce architecture, OAuth flows, ERDs, integration sequences, or Agentforce structure. TRIGGER when: user says "diagram", "visualize", "ERD", or asks for sequence diagrams, flowcharts, class diagrams, or architecture visualizations in Mermaid. DO NOT TRIGGER when: user wants PNG/SVG image output (use generating-visual-diagrams), or asks about non-Salesforce systems.