AB youtube-data-cli
Full YouTube Data API v3 CLI covering all 20 resources: search, channels, videos (upload/update/delete/rate), playlists, playlist items, comments, subscriptions, captions (upload/download), thumbnails, activities, channel sections, channel banners, members, memberships levels, watermarks, and more. Triggers: "YouTube", "YouTube search", "YouTube playlists", "YouTube comments", "YouTube subscriptions", "search videos", "playlist management", "video comments", "upload video", "video captions", "subtitles", "YouTube thumbnail", "channel members", "video categories", "channel banner", "YouTube watermark", "rate video", "like video", "channel sections", "YouTube activities".
As a process B 69/100 · Nearly there — weak spots: when it triggers, inputs and preconditions, running it twice
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
- A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.
Guard findings · 0
✓ No critical or high findings
Files scanned: 2. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
description-no-whendescription does not say WHEN to use the skill (no "use when")
Process rating: all ten parameters 69/100
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 14 mutating operations with no state check
- 60Result and completion. Output format stated, no completion criterion
- 100Tools and files. No external tools needed
- 100Steps. 31 steps
- 100Failures and branches. 1 branches, has a failure section
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 2607 tokens
Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.
Quality signals
- +4Description does not say when NOT to use the skill (false activations)
- +1No license
- +2Single-language instructions
- +5Description quotes 20 example trigger phrases
- +3Description length 678: enough signal without eating the budget
- +4Structure: 32 headings
- +3Step-by-step instructions: 31 items
- +3Output format is stated explicitly
- +4Has examples (21 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 80.