agentleFS
Mathews-TomMathews-Tom/armory/skills/youtube-search/SKILL.md

youtube-search

Skill340 starsChanged 8 months agoMITView on GitHub

Search YouTube by keyword and return structured video metadata (title, URL, channel, views, duration, date) via yt-dlp. No API keys. Triggers on: "search youtube", "find youtube videos", "top youtube videos on", "trending videos on", "youtube results for", "yt search", "/yt-search".

13 other projects use a version of this.

Adopted by

Most recently taken up by

Used with

Projects with it also use youtube-transcript.

Other files people use alongside this one.

Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
  • dandacompanySkill

    youtube-transcript

    Extract YouTube video transcripts/subtitles using yt-dlp. Handles rate limiting, auto-generated captions, multiple languages, and VTT parsing.

    Also in 4 projects that use this

The file

We split this skill into the rules it gives an agent

1 rule. 0 are common, 0 are distinctive, and 1 is very specific to this project.

  • 0

    Common

    Most of the 12 edited versions we read keep these.

  • 0

    Distinctive

    This author's own choices. Worth a look.

  • 1

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Search YouTube by keyword and return structured video metadata — title, URL, channel, views, duration, upload date.

    line 13

“Common” is measured: kept by at least 6 in 10 of the 12 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

YouTube Search

Search YouTube by keyword and return structured video metadata — title, URL, channel, views, duration, upload date. Uses yt-dlp for scraping with no API keys or OAuth required.

Prerequisites

uv tool install yt-dlp

Verify:

yt-dlp --version

Usage

Basic Search

yt-dlp "ytsearch10:claude code skills" --dump-json --flat-playlist --no-warnings 2>/dev/null \
  | jq -r '[.title, .url, .channel, .view_count, .duration_string, .upload_date] | @tsv'
  • ytsearch10: — search YouTube, return 10 results (adjust number as needed)
  • --dump-json — output metadata as JSON
  • --flat-playlist — don't download, just list
  • --no-warnings — suppress non-error output

Structured JSON Output

yt-dlp "ytsearch5:claude code mcp servers" \
  --dump-json --flat-playlist --no-warnings 2>/dev/null \
  | jq '{
    title: .title,
    url: .url,
    channel: .channel,
    views: .view_count,
    duration: .duration_string,
    upload_date: .upload_date,
    description: (.description // "" | .[0:200])
  }'

Search with Sorting

yt-dlp does not support server-side sort. To sort by views or date, capture all results and sort client-side:

# Sort by view count (descending)
yt-dlp "ytsearch20:AI agents 2026" \
  --dump-json --flat-playlist --no-warnings 2>/dev/null \
  | jq -s 'sort_by(-.view_count) | .[:10][] | {title, url, channel, views: .view_count}'
# Sort by upload date (newest first)
yt-dlp "ytsearch20:claude code tutorial" \
  --dump-json --flat-playlist --no-warnings 2>/dev/null \
  | jq -s 'sort_by(-.upload_date) | .[:10][] | {title, url, channel, upload_date}'

Search Result Count

The number after ytsearch controls how many results to fetch:

PatternResults
ytsearch5:query5 results
ytsearch10:query10 results (default recommendation)
ytsearch20:query20 results
ytsearch50:query50 results (slow, may hit rate limits)

Recommendation: Fetch 15-20 results, then filter/sort client-side to the top N the user wants. This provides enough data for meaningful sorting without being excessive.

Workflow

User provides search query
        |
        v
+---------------------+
|  Step 0: Deps check |
+----------+----------+
           v
+---------------------+
|  Step 1: Search     |
|  (yt-dlp ytsearch)  |
+----------+----------+
           v
+---------------------+
|  Step 2: Parse JSON |
|  (jq formatting)    |
+----------+----------+
           v
+---------------------+
|  Step 3: Present    |
|  results to user    |
+---------------------+

Step 1: Execute Search

yt-dlp "ytsearch${COUNT}:${QUERY}" \
  --dump-json --flat-playlist --no-warnings 2>/dev/null

Step 2: Parse and Format

Extract relevant fields with jq. The full metadata object from yt-dlp contains many fields; the useful subset for search results:

FieldDescription
.titleVideo title
.urlFull YouTube URL
.channelChannel name
.view_countTotal views (integer)
.duration_stringDuration as H:MM:SS or MM:SS
.upload_dateUpload date as YYYYMMDD
.descriptionVideo description (can be long — truncate)
.like_countLikes (may be null)
.comment_countComments (may be null)

Step 3: Present Results

Format as a markdown table for the user:

yt-dlp "ytsearch10:${QUERY}" \
  --dump-json --flat-playlist --no-warnings 2>/dev/null \
  | jq -s 'sort_by(-.view_count) | .[] | "| \(.title[:60]) | \(.channel) | \(.view_count) | \(.duration_string) | \(.upload_date) |"' -r

Prefix with a header row:

| Title | Channel | Views | Duration | Date |
|-------|---------|-------|----------|------|

Advanced Patterns

Filter by Duration

# Only videos longer than 10 minutes (600 seconds)
yt-dlp "ytsearch20:deep dive AI agents" \
  --dump-json --flat-playlist --no-warnings 2>/dev/null \
  | jq -s '[.[] | select(.duration >= 600)] | sort_by(-.view_count) | .[:10][]'

Filter by Recency

# Only videos from the last 30 days
CUTOFF=$(date -v-30d +%Y%m%d 2>/dev/null || date -d "30 days ago" +%Y%m%d)
yt-dlp "ytsearch20:claude code" \
  --dump-json --flat-playlist --no-warnings 2>/dev/null \
  | jq -s --arg cutoff "$CUTOFF" '[.[] | select(.upload_date >= $cutoff)] | sort_by(-.view_count) | .[]'

Channel-Specific Search

# Search within a specific channel
yt-dlp "ytsearch10:skills site:youtube.com/c/ChannelName" \
  --dump-json --flat-playlist --no-warnings 2>/dev/null

Or use the channel URL directly:

yt-dlp "https://www.youtube.com/@ChannelName/search?query=skills" \
  --dump-json --flat-playlist --no-warnings 2>/dev/null

Extract URLs Only (for Piping)

# Get just URLs for feeding into other tools (watch, notebooklm)
yt-dlp "ytsearch10:claude code MCP" \
  --dump-json --flat-playlist --no-warnings 2>/dev/null \
  | jq -r '.url'

Composability

This skill produces URLs and metadata that feed into other skills:

  • watch: Pass URLs for transcript concepts, timestamped visual evidence, and question-driven video analysis
  • notebooklm: Pass URLs as sources via notebooklm source add "URL"

Example pipeline (manual steps, not automated):

  1. /yt-search — discover 10 relevant videos
  2. User reviews and selects videos
  3. Feed selected URLs into notebooklm source add or watch

Error Handling

ErrorCauseResolution
No resultsQuery too specific or misspelledBroaden the search terms
Empty JSONyt-dlp rate limited by YouTubeWait a few minutes, retry
yt-dlp: command not foundNot installeduv tool install yt-dlp
Partial resultsSome videos geo-blocked or privateNormal behavior; results are best-effort
TimeoutNetwork or YouTube slownessReduce result count or retry

Limitations

  • No server-side sorting: YouTube search results come in relevance order. Sorting by views or date requires fetching extra results and sorting client-side.
  • Rate limiting: Aggressive scraping (50+ results, rapid repeated searches) may trigger YouTube rate limits. Space requests apart.
  • Metadata completeness: Some fields (.like_count, .comment_count) may be null for certain videos. Always handle nulls in jq filters.
  • No authentication: Uses public YouTube data only. Age-restricted or private videos are excluded from results.
  • Search relevance: YouTube's search algorithm determines initial ordering. Results may not match exact expectations.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.