CtrlK
BlogDocsLog inGet started
Tessl Logo
SkillPublic

youtube-comments-api-skill

This skill helps users extract structured video list data and comment data from YouTube using the BrowserAct API. The Agent should proactively apply this skill when users request searching for YouTube videos and their comments, analyzing viewer sentiment for a specific video topic, gathering audience feedback on AI or automation, extracting a list of top videos and their viewer reactions, compiling YouTube video data along with user opinions, retrieving competitor video titles and related audience discussions, monitoring public response to specific YouTube search keywords, summarizing comments from search results for market research, tracking viewer engagement metrics and replies for trending topics, collecting YouTube video URLs and author details alongside community discussions, or automating the extraction of YouTube comments without manual scraping.

Quality

87%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide
SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

81%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 is highly actionable with a clear, validated workflow and a single clean script reference. Its main weakness is conciseness: marketing-style Features framing and an over-long use-case list consume tokens that do not aid execution.

Suggestions

Cut the Features section's competitive/marketing claims ('Zero Hallucination', 'Extremely High Cost-Efficiency') to one-line factual notes or remove them; Claude gains no execution value from the puffery.

Compress the 10-item Typical Use Cases list to 3-4 representative cases, or move it to a separate reference file to reduce inline token load.

Add a pre-flight note confirming the script path resolves (./scripts/youtube_comments_api.py) so the validation chain is explicit from the start.

DimensionReasoningScore

Conciseness

The body is mostly efficient but includes padded marketing prose in Features ('Zero Hallucination', 'Extremely High Cost-Efficiency'), emoji-laden headers, and a 10-item use-case list that could be trimmed, matching the level-3 anchor of 'mostly efficient but includes some unnecessary explanation.'

3 / 5

Actionability

It provides a copy-paste invocation command with exact positional args, a typed parameter table with defaults/examples, named output fields, and a specific error sentinel ('Invalid authorization') with a decision tree, matching the level-5 anchor for fully executable, copy-paste-ready guidance.

5 / 5

Workflow Clarity

The sequence (check API key -> invoke -> monitor timestamped status logs -> error decision tree with one-retry feedback loop) has explicit checkpoints and an error-recovery loop appropriate to this batch extraction task, matching the level-5 anchor.

5 / 5

Progressive Disclosure

Content is well-organized into clearly labeled sections with a single one-level-deep reference to ./scripts/youtube_comments_api.py and no nested references, matching the level-4 anchor for good structure with minor organization gaps rather than the level-5 multi-reference ideal.

4 / 5

Total

17

/

20

Passed

Description

90%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 is strong: third-person voice, explicit 'what' and 'when' guidance, and rich natural trigger phrases that sharply distinguish the skill. Its only weakness is a narrow action vocabulary ('extract') that keeps specificity from reaching the top anchor.

Suggestions

Broaden the 'what' clause to enumerate 2-3 distinct concrete actions (e.g., 'extract video lists, retrieve comments, and compile engagement metrics') rather than restating 'extract' across clauses.

Tighten the long 'when' enumeration; the ten near-synonymous clauses add length without proportional trigger value.

DimensionReasoningScore

Specificity

The description names the domain ('extract structured video list data and comment data from YouTube using the BrowserAct API') but relies on a single core action verb, so it names 1-2 concrete actions without a comprehensive action list, matching the level-3 anchor rather than the multi-action level-5.

3 / 5

Completeness

It explicitly answers both 'what' (extract structured video list and comment data via BrowserAct API) and 'when' ('The Agent should proactively apply this skill when users request...') with concrete trigger phrases, matching the level-5 anchor.

5 / 5

Trigger Term Quality

It offers comprehensive natural trigger phrasing with synonyms ('searching for YouTube videos and their comments', 'analyzing viewer sentiment', 'summarizing comments... for market research', 'automating the extraction of YouTube comments without manual scraping'), matching the level-5 anchor's coverage of natural user terms.

5 / 5

Distinctiveness Conflict Risk

The YouTube-comments-via-BrowserAct niche with 'without manual scraping' framing is clearly distinct and unlikely to trigger the wrong skill, matching the level-5 anchor for a clear niche with minimal conflict risk.

5 / 5

Total

18

/

20

Passed

Validation

87%

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

Validation — 14 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

metadata_version

'metadata.version' is missing

Warning

metadata_field

'metadata' should map string keys to string values

Warning

Total

14

/

16

Passed

Repository

browser-act/skills

Path

solutions/video-platforms/youtube-comments-api-skill/SKILL.md

Reviewed

Table of Contents

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.