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multi-video-synthesis

Performs high-density targeted extraction across 10+ videos to map semantic landscapes, consensus, and controversies.

53

Quality

59%

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SecuritybySnyk

Low

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tessl review fix ./python/agents/youtube-analyst/youtube_analyst/skills/multi-video-synthesis/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

65%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The body presents a clear, well-sequenced pipeline that names its tools, thresholds, fallbacks, and output artifacts, and it stays admirably lean. Its weaknesses are a batch operation with no validation/verification checkpoints, vague ranking criteria for the 'Return on Attention' filter, and a few over-claim flourishes that could be cut.

Suggestions

Add explicit validation checkpoints, e.g. after transcript retrieval verify each video has content (fall back to metadata if not), and before delivering the report verify every timestamp URL is within the video's duration.

Make the 'Return on Attention' ranking concrete: specify how engagement metrics, keyword relevance, and channel authority combine (e.g., rank by normalized view-to-like ratio and keyword match count) instead of the current vague criteria.

Remove the '(ATTENTION GUARDIAN)' aside, 'absolute truth', and the 'does not exist elsewhere on the web' flourish; replace with a one-line statement of the pipeline's goal.

DimensionReasoningScore

Conciseness

The body is a lean ~25-line numbered workflow with tool names and parameters, assuming Claude's competence throughout. Minor over-explanation could be trimmed: the '(ATTENTION GUARDIAN)' aside, 'absolute truth', and the closing flourish 'a new, high-density knowledge artifact that does not exist elsewhere on the web' are padding. This fits 'efficient; minor instances of over-explanation' rather than the noticeably-verbose anchor 3.

4 / 5

Actionability

Concrete elements exist (`search_youtube` with `max_results=15`, named MCP tools, a '3+ creators' consensus threshold, fallback to metadata when transcripts fail, named report artifacts), but key execution details are missing: how 'Return on Attention' is actually computed or weighted, how `get_video_details`/`calculate_engagement_metrics` are invoked, and what the briefing structure looks like. This matches 'some concrete guidance but incomplete; missing key details'.

3 / 5

Workflow Clarity

The six steps are clearly numbered and sequenced with a fallback path (transcript unavailable -> metadata), but there is no validation or verification step for this batch operation (e.g., verifying transcripts were actually retrieved, checking generated timestamp URLs, confirming engagement data before ranking). Per the guidelines, a batch workflow without validation checkpoints is capped at 3.

3 / 5

Progressive Disclosure

The skill is under 50 lines, self-contained, and needs no external reference files (none are bundled); its numbered execution steps, bolded step titles, and clearly labeled report sections constitute well-organized structure. Per the simple-skill guideline, this earns a 5 with just well-organized sections.

5 / 5

Total

15

/

20

Passed

Description

53%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description identifies a distinctive niche (large-scale multi-video synthesis) but is held back by buzzword-heavy phrasing ('high-density targeted extraction', 'semantic landscapes'), missing natural trigger phrases, and the complete absence of a 'Use when...' clause. It reads more like a mission statement than a trigger-optimized skill description.

Suggestions

Add an explicit trigger clause, e.g. 'Use when the user asks to research, summarize, or compare multiple (10+) videos, YouTube videos, or creator viewpoints.'

Replace buzzword phrases ('high-density targeted extraction', 'map semantic landscapes') with plain concrete capabilities like 'watch/read transcripts of many videos and identify consensus, controversies, and unique insights'.

Include natural user phrasings and synonyms (YouTube, video research, summarize videos, compare creators' takes) so the description matches what users actually say.

DimensionReasoningScore

Specificity

Phrases like 'Performs high-density targeted extraction across 10+ videos to map semantic landscapes, consensus, and controversies' name the domain and two actions (extraction, mapping consensus/controversies), but 'high-density targeted extraction' and 'semantic landscapes' lean on buzzwords rather than concrete capabilities. It sits between the '1-2 concrete actions' (3) and 'several specific actions' (4) anchors, closer to 3 because the actions are generic-sounding despite specific scope.

3 / 5

Completeness

The 'what' is stated (extraction across 10+ videos to map consensus/controversies) but there is no 'Use when...' clause or any equivalent trigger guidance, so per the guidelines completeness is capped at 3.

3 / 5

Trigger Term Quality

'videos', 'consensus', and 'controversies' are relevant keywords, but common natural phrases a user would say are absent: 'summarize videos', 'YouTube', 'video research', 'compare videos', 'watch videos'. This matches 'some relevant keywords but missing common variations or synonyms'.

3 / 5

Distinctiveness Conflict Risk

'10+ videos', 'consensus', and 'controversies' carve out a fairly distinct multi-video synthesis niche with minimal conflict risk against generic video-summarization or research skills. Minor overlap risk remains with single-video summarization or general research skills, matching 'mostly distinct; minor overlap risk'.

4 / 5

Total

13

/

20

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
google/adk-samples
Reviewed

Table of Contents

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