muapi-animal-video-generator

Create a hilarious and ultra-realistic video of an anthropomorphic animal acting like a human vlogger in a real-world setting.

Quality

66%

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Securityby

Passed

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tessl review fix ./library/motion/animal-video-generator/SKILL.md

Quality

Content

78%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 delivers a tight, actionable two-phase workflow with concrete muapi commands, explicit prompts, and a clear user-approval checkpoint between image and video generation. The main gap is the absence of failure-handling guidance and fully literal command lines.

Suggestions

Add a brief error-recovery step for failed generation (e.g., re-run with an alternate model or check the request status) to strengthen the workflow's feedback loop.

Show at least one phase as a literal copy-paste command line with flags (e.g. `muapi image generate --model nano-banana --prompt "..." --aspect 9:16`) to reach fully executable guidance.

Remove the verbatim repetition of the frontmatter description as the bold subheading to tighten conciseness.

Dimension	Reasoning	Score
Conciseness	The body is efficient with no over-explanation of concepts Claude already knows; the only minor trim is the description being repeated verbatim from the frontmatter as a bold heading, fitting the score-4 anchor of efficient content with minor instances that could be trimmed.	4 / 5
Actionability	Provides concrete CLI commands ("muapi image generate", "muapi video generate"), specific model IDs, full prompts, and a curl fallback, but commands are described with their parameters rather than given as literal copy-paste command lines, matching the score-4 anchor of mostly executable guidance with minor gaps.	4 / 5
Workflow Clarity	Two phases are clearly sequenced with an explicit approval checkpoint ("After generating the image, present it to the user" / "Once the image is approved"), but there is no failure-recovery loop for a failed generation, fitting the score-4 anchor of a clear sequence with most checkpoints present and minor gaps.	4 / 5
Progressive Disclosure	The skill is roughly 50 lines, single-purpose, and well-organized into clearly headed sections (Inputs, Steps, Trigger Keywords, Notes) with no need for external references, so under the rubric's simple-skill exception progressive disclosure scores 5 on well-organized sections alone.	5 / 5
	Total	17 / 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 vividly conveys a distinctive, single-purpose deliverable but omits any "when to use" trigger guidance and lists only one action, capping both completeness and trigger-term quality. Adding a "Use when..." clause with natural trigger phrases would lift the weaker dimensions.

Suggestions

Append a "Use when..." clause naming concrete user triggers (e.g. "Use when the user asks for a funny animal vlogger video, a talking animal clip, or an anthropomorphic animal in a real-world setting").

Broaden trigger term coverage with natural synonyms users actually say, such as "funny animal video", "talking animal", or "animal vlog".

Optionally surface the multi-action nature (generate image, then animate with lip-sync) so the description reflects several concrete actions rather than one.

Dimension	Reasoning	Score
Specificity	Names the domain vividly and one concrete action ("Create a ... video") with rich output detail, but lists only a single action rather than multiple concrete capabilities, matching the score-3 anchor of domain plus 1-2 actions.	3 / 5
Completeness	Clearly answers "what" (create an anthropomorphic animal vlogger video) but provides no "Use when..." clause or equivalent trigger guidance, so per the rubric guideline completeness is capped at 3 with a clear "what" and missing "when".	3 / 5
Trigger Term Quality	Contains relevant natural terms ("animal", "video", "vlogger") but misses common variations or synonyms users would say (e.g. "funny animal video", "monkey"), fitting the score-3 anchor of some relevant keywords with missing variations.	3 / 5
Distinctiveness Conflict Risk	The anthropomorphic-animal-vlogger niche is highly specific with minimal conflict risk, but the absence of explicit trigger phrases keeps it just below the score-5 anchor, landing at "mostly distinct; minor overlap risk".	4 / 5
	Total	13 / 20 Passed

Validation

93%

Warnings & errors only

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

Validation — 15 / 16 Passed

Validation for skill structure

Criteria	Description	Result
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	15 / 16 Passed

Repository: SamurAIGPT/Generative-Media-Skills
Path: library/motion/animal-video-generator/SKILL.md
Commit: 74df8cb

Reviewed: 5 days ago

Table of Contents

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