Skill · Media
Web media getter
One query across free image / video / GIF APIs (stock + historical/archival + GIF engines), returning normalized, license-tagged results with optional top-K download + attribution sidecar. The retrieval peer to local semantic search and generative media.
How to use it
- Start your plan and connect your AI once
- Ask for the task in your own words, or say it directly:
Use the Web media getter skill to help me with this.Without a connection: copy the SKILL.md below into your AI's project instructions.
When to Use
Use when a task needs a REAL or ARCHIVAL photo / clip (hero, texture, reference, historical footage) or a reaction / animated GIF, rather than a generated one — fan out across free image/video/GIF sources in one query and download license-tagged results.
_Source: connerkward/web-media-getter-skill (MIT)._
web-media
Query many free image/video sources in one fan-out, get a normalized result list, optionally download top-K with an attribution sidecar. Zero-dep stdlib script.
Script: webmedia.py (in this dir). Keys: PEXELS_API_KEY, PIXABAY_API_KEY in central/.env (optional — the 5 no-key sources work without them).
Sources
| Source | Key? | Best for | Media |
|---|---|---|---|
| openverse | none | CC web images (Flickr, museums) | image |
| wikimedia | none | factual / historical / landmark photos | image |
| internetarchive | none | historical/archival images + films | image, video |
| loc | none | historical US prints/photos | image |
| nasa | none | space imagery + video | image, video |
| pexels | free key | modern stock photos + short video clips | image, video |
| pixabay | free key | modern photos/illustrations + short clips | image, video |
| klipy | free key | GIFs — recommended (free, unlimited, Tenor drop-in) | gif |
| giphy | free key | GIFs — biggest library (prod key needs approval) | gif |
GIF sources fire only with --type gif. Keys: KLIPY_API_KEY, GIPHY_API_KEY in central/.env. (tenor adapter removed — Google EOL'd the API 2026-06-30.) klipy is the one to get (free + unlimited); its adapter is unverified — assumes Tenor-compatible request/response; verify against docs.klipy.com when you key it. webmedia.py "shrug" --type gif --count 6 --json
Usage
webmedia.py "1950s street scene" --type image --count 8 --json
webmedia.py "rocket launch" --type video --source nasa,internetarchive
webmedia.py "car factory 1930s" --source all --download --out /tmp/cars
--source all(default) |nokey(no-key only) | comma list (wikimedia,pexels)--type image|video·--count N·--json·--download --out DIR--downloadfetches each result's direct media URL and writesattribution.json
(source, author, license, url, page_url) alongside the files.
Record schema
{source, title, url, thumb, dl, page_url, author, license, w, h, type} — dl is the directly-downloadable media URL (None when only a page exists).
The video caveat (important)
Archival sources (Internet Archive, Europeana, LoC) host whole films/documentaries, not single shots. So:
- Modern single clip →
pexels/pixabay(born as short clips, direct MP4). Done. - Historical single shot → retrieve the IA film here, then extract the shot:
- Twelve Labs Marengo search (free 600 min) — pass the IA public MP4 URL, get a
- or PySceneDetect (free, local) to cut the film into shots, then rank keyframes
timestamped moment for "car on assembly line", clip with ffmpeg. Semantic, cheap.
with CLIP via the muser skill. Fully offline.
Audio: freesound + audio QA
webmedia.py is image/video. For sound effects (real, CC-licensed) and for judging audio (since Claude can't hear), two sibling scripts live in central/scripts/:
freesound-fetch.py "<query>" [count] [max_sec] [out_dir]— searches freesound.orgaudio-judge.py <file> "<target>"— sends the clip to OpenAIgpt-audio
and downloads short hq-mp3 previews. Prints one JSON line per file with license/user for attribution. Key: FREESOUND_API_KEY in central/.env (token-based read; full originals would need OAuth — previews suffice for SFX).
(audio-native) and returns JSON {heard, score, matches, suggestion}, enabling a generate/fetch → judge → iterate loop. Auto-sources a real sk- OPENAI_API_KEY from .env (ignores a local lm-studio stub env var). Pads sub-2s clips so the speech-tuned model doesn't refuse. Caveat: it reliably describes audio and filters obvious mismatches, but it is NOT a trustworthy judge of subjective qualities like "grating" — it labels nearly any beep "sharp/high-pitched". Use it to cull, not to make the final aesthetic call; confirm by ear.
Where this fits
This is the internet-retrieval capability — peer to muser (local semantic search) and fal (generate). A future media router would fan out across all three and rank candidates by relevance (CLIP), handing aesthetic spreads to lookdev. Don't build that router until the model demonstrably mis-routes without it.
Limitations
- Results depend on third-party API availability, quotas, credentials, and license metadata quality.
- License tags and attribution fields must still be reviewed before commercial or public use.
- Relevance ranking can find plausible assets, but final aesthetic fit, brand safety, and audio suitability require human inspection.