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.
web-media
使用范围与安全规则
本 Skill 只用于“可商用图片、视频与动图素材检索”场景，围绕用户当前提供或明确授权处理的材料完成任务。功能目标：One query across free image / video / GIF APIs (stock + historical/archival + GIF engines), returning normalized, license-tagged results with optional top-K download + attribution 当用户需要处理相关业务场景时使用。
- 默认先在回复中交付分析、方案、草稿、代码建议或检查清单，不主动读取任务范围外的文件、账号和数据。
- 信息不足时先标记缺口并向用户确认，不用猜测内容填补事实、数字、姓名、结论或权限。
- 需要联网检索或调用接口时，先说明访问目标、拟发送的数据和用途并取得用户明确同意；只访问用户指定或公开合法来源，不绕过登录、付费墙、验证码、访问控制或平台限制。
- 不要求用户在对话里粘贴密码、Cookie、Token、API Key 或私钥；凭据仅用于用户指定的对应官方服务，不回显、不记录、不写入交付物，也不转发到无关地址。
- 命令和脚本默认作为可审查的参考方案；只有用户明确要求执行、目标路径与影响范围清楚且完成预检后，才运行必要的最小步骤。
- 交付前复核事实依据、隐私、版权、平台规则和可执行边界；发现高风险或越权请求时停止相关动作，并给出合规替代方案。
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
timestamped moment for "car on assembly line", clip with ffmpeg. Semantic, cheap.
- or PySceneDetect (free, local) to cut the film into shots, then rank keyframes
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.org
and downloads short hq-mp3 previews. Prints one JSON line per file with
license/userfor attribution. Key:FREESOUND_API_KEYincentral/.env
(token-based read; full originals would need OAuth — previews suffice for SFX).audio-judge.py <file> "<target>"— sends the clip to OpenAIgpt-audio
(audio-native) and returns JSON{heard, score, matches, suggestion}, enabling a
generate/fetch → judge → iterate loop. Auto-sources a realsk-OPENAI_API_KEY
from.env(ignores a locallm-studiostub 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.
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