Td Trend Scout

td-trend-scout — single-surface hype scouting procedure

This skill is loaded by a td-trend-scout sub-agent. You receive one surface from the orchestrator and produce one file: _workspace/hype-scout/01_scout_.md. You do not synthesize across surfaces — that's td-hype-synthesizer's job.

Procedure

Step 1 — Open your scratchpad (immediately)

Write the file header before any web work, so a network failure mid-run leaves usable partial output:

mkdir -p _workspace/hype-scout

Then Write the file with this header (replace ``):

# Hype scout — 

**Surface:** 
**Scout window:** 2025-Q3 → 2026 (preferentially), with documented revivals of older trends allowed.
**Run:** 

## Trend candidates

Append each candidate as you confirm it (don't batch). If your run is cut off, the orchestrator can resume from this file.

Step 2 — Map your surface

Use the surface map below to know where to look. Don't search everywhere — go deep on the channels that matter for your surface.

community-showcase — what artists are shipping

• TD Forum showcase: https://forum.derivative.ca/c/community-showcase/
• Instagram: search #touchdesigner, #touchdesignerart, #touchdesignerartist, #touchdesigner099
• Vimeo: TouchDesigner tag, derivative group
• Behance: TouchDesigner projects, filter by Recent
• x.com / Twitter: from:elekktronaut OR from:dotsimulate OR from:paketa12 etc., #touchdesigner
• Are.na: TD channels (touchdesigner, td-sketches)

Look for: recurring techniques across multiple posts in the last ~6 months; what they're making, not who made it.

tutorials — what is being taught

• YouTube channels (search their last 6-12 months of uploads):
• elekktronaut (Bileam Tschepe) — high-end tutorials, often front-runs trends
• Paketa12 — practical effects
• The Interactive & Immersive HQ — pro patterns, installations
• dotsimulate — AI bridges (StreamDiffusion, ComfyUI)
• Crystal Jow — generative + audioreactive
• Matthew Ragan — fundamentals + recent advanced work
• Acid Boi, Yeyou Studio, Noones Lab
• Skillshare / Domestika TD course catalog — what's selling
• Recent blog posts: derivative.ca/wiki, Medium TD tag

Look for: techniques covered by 3+ channels in 6 months = a hot front-running trend.

generative-ai — TD ↔ AI crossover

• dotsimulate's TouchDiffusion / StreamDiffusion TOX (search recent demos)
• ComfyUI-in-TD bridges (Spout/NDI/OSC, "comfyui touchdesigner")
• Realtime ML in TD: depth (MiDaS, Depth Anything), pose (MediaPipe, BlazePose), style transfer, segmentation
• ControlNet rigs driven from TD
• Audio-to-video AI (Stable Audio + TD, etc.)
• LCM / Lightning models real-time
• Forum threads on AI integration (forum.derivative.ca — Components & Tools, Beginners)

hardware-interactive — physical inputs

• LiDAR: Livox HAP/Tele, Ouster OS-1, iPhone LiDAR via Record3D / WebSocket
• Depth cameras: RealSense D4xx/L515, Kinect Azure (and post-Azure alternatives)
• Hand tracking: Leap Motion 2 / Ultraleap, MediaPipe Hands via NDI/Spout
• Body pose: MediaPipe BlazePose, OpenPose, BlazePose-via-NDI
• Audio interfaces / Ableton Link / MIDI: trending mappings, TouchOSC profiles, Stream Deck workflows
• Sensors: capacitive (Bare Conductive), IR, ToF, eye tracking (Tobii)
• Recent installation case studies in showcases

vfx-aesthetics — visual languages

For each candidate aesthetic, look across showcase + Instagram for recurrence:

• ferrofluid / metaballs / liquid metal / chrome
• raymarched volumetrics, SDF scenes
• particle systems with feedback loops, slit-scan
• datamosh / glitch revival, pixel-sort
• kinetic typography, type-as-form
• scan-line / CRT / VHS aesthetic
• retro-cyber, Y2K revival
• point-cloud / 3D-scan / photogrammetry aesthetic
• generative gradients, brutalist-data dashboards
• low-bit / dithered / Bayer
• voronoi / cellular / organic growth
• liquid-metal / chrome
• isometric pixel / voxel

Step 3 — For each candidate trend, do the vet pass

Before writing an entry, check three things:

1. Recency & evidence. Do I have ≥2 citations from 2025-2026 (or documented revival posts)? URLs that resolve, not just memory. If not, drop or downgrade.
2. Tool shape in tdmcp. Can I name the layer + the TD operators or bridge endpoint? Use grep against the repo to confirm operators exist in the KB:

``bash grep -irn "realsense\|kinect\|pointCloud" src/knowledge/data/ | head grep -irn "create_.*audio\|create_.*particle" src/tools/ | head grep -irn "" src/tools/ src/knowledge/data/ docs/ROADMAP.md ``

1. tdmcp coverage. Search src/tools/ and recipes/ for existing equivalents:

• NOT-COVERED: nothing close — clean new tool.
• PARTIAL: related tool exists but doesn't fully cover the trend (e.g. create_audio_reactive covers audio→visual, but not "Ableton-Link locked phrase morph").
• COVERED: it already exists — note the existing tool name; consider as EXTENSION if the trend adds a preset/parameter.

Step 4 — Write the entry

Append to your scratchpad in this exact format:

### . 

- **What artists are doing:** 1-3 sentences, concrete.
- **Why it's hyped:** 1 sentence about *why now*.
- **Evidence:**
  -  — 
  -  — 
  - (optional)  — 
- **Hype intensity:** High / Medium / Low
- **Recency tag:** e.g. `Q4-2025`, `2026`, `2024-revival`
- **Suggested tdmcp tool:** `create_` — Layer  — touches operators `` (cite KB path or note `UNVERIFIED — probe live`).
- **Build-ease guess:** S / M / L (S=hours, M=day, L=multi-day or new bridge endpoint)
- **tdmcp coverage:** NOT-COVERED / PARTIAL — existing `` / COVERED — existing ``
- **Cross-surface footnote:** (optional) e.g. "also appears in `tutorials`"

Step 5 — Tally and close

End the file with a one-line tally:

---
**Tally:** N candidates — Hype H/M/L: `` — Coverage NOT/PART/COV: `` — Build S/M/L: ``

If the file is tagged PARTIAL-DUE-TO-NETWORK, say so at the top.

Hype lenses (use multiple, not just one)

When you scan a surface, run each candidate through at least 2 of these lenses to confirm it's really trending:

| Lens | Question | |---|---| | Recurrence | Is this technique appearing in 3+ recent posts/videos by different creators? | | Front-runner | Is a respected tutorial channel (elekktronaut, dotsimulate) teaching it now? | | Cross-tool | Is it bridging TD with another hot tool (ComfyUI, Ableton, Notch, Unreal)? | | Hardware unlock | Is it riding a new hardware capability (LiDAR cheap now, iPhone depth, M-series GPU)? | | Aesthetic moment | Is this visual language showing up across genres (clubs, brand work, art installations)? | | AI moment | Is this trend riding the real-time ML wave (StreamDiffusion, Depth Anything, etc.)? |

Single-lens trends are usually weak signal — note them but score Hype: Low. Multi-lens trends (e.g. front-runner + cross-tool + AI moment) are strong signal — score Hype: High.

Citation rules (non-negotiable)

• Real URLs only. Do not paraphrase from memory.
• At least 2 citations per entry. If you can only find 1, lower confidence and mark EVIDENCE-WEAK.
• Mix sources. Two posts from the same Instagram account are weaker than one Instagram + one YouTube.
• Date when possible. Quote upload/post dates in the 1-line description ("Sept 2025 tutorial").

Working tools

• WebSearch to find recent posts/videos/threads on your surface.
• WebFetch to verify a URL is live and pull a 1-line summary.
• Bash (grep/find) + Read to check tdmcp coverage (src/tools/, src/knowledge/data/, docs/ROADMAP.md, recipes/).
• Write (incremental append via Edit after the initial header Write).

If WebSearch/WebFetch aren't available, do what you can with cached knowledge but tag the file PARTIAL-DUE-TO-NETWORK at the top and lower every entry's confidence by one notch.

What not to do

• Don't scout outside your assigned surface (write cross-surface footnotes instead).
• Don't pad to a count — 6 high-confidence entries beat 15 weak ones.
• Don't claim hype without citations. "Everyone is doing X" without 2 URLs is not an entry.
• Don't invent operators. Cite the KB (src/knowledge/data/) or mark UNVERIFIED — probe live.
• Don't synthesize. You scout one surface; the synthesizer dedupes across them.

Re-invocation

If _workspace/hype-scout/01_scout_.md already exists:

1. Read it first.
2. Apply only the requested change — refresh citations, deepen a category, re-check coverage against an updated tree.
3. Preserve existing numbering where it doesn't conflict.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: hybridlabor-api
• Source: hybridlabor-api/bdb-dev-optimized-agent-skills
• License: Apache-2.0

Install and usage instructions live in the source repository linked above.