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muapi-workflow

Build, run, and visualize multi-step AI generation workflows. The AI architect translates natural language descriptions into connected node graphs — chain image generation, video creation, enhancement, and editing into automated pipelines.

60

Quality

70%

Does it follow best practices?

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SecuritybySnyk

High

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tessl review fix ./library/workflow/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

67%

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 concrete, executable commands and a clear core workflow, but it is somewhat redundant across sections and lacks explicit validation/feedback checkpoints for its generation runs. Progressive disclosure is present via real bundle scripts but undermined by repeated inline CLI content.

Suggestions

Add explicit validation checkpoints to the run workflow (e.g. poll 'muapi workflow status <run_id>' and confirm completion before calling 'muapi workflow outputs'), with a fix/retry loop on failure.

Consolidate the duplicated CLI invocations from the Examples and CLI Reference sections into a single reference block to remove redundancy.

Clearly signal the bundle scripts at the point of use (e.g. link generate-workflow.sh next to the create step) rather than only listing them in the Core Operations overview.

DimensionReasoningScore

Conciseness

The body is mostly efficient with concrete commands, but several sections repeat the same CLI invocations (create/get/execute appear in Core Operations, the Building protocol, Examples, and the CLI Reference), adding redundancy that could be tightened.

2 / 3

Actionability

Commands are concrete and copy-paste ready throughout (e.g. 'muapi workflow execute <workflow_id> --input "node1.prompt=..." --download ./outputs'), with real flag values and examples rather than pseudocode.

3 / 3

Workflow Clarity

The Building-a-Workflow protocol is numbered and sequenced, but for batch/generation operations there are no explicit validation checkpoints or error-recovery feedback loops (e.g. verify a run succeeded before downloading outputs); the rubric notes this caps workflow clarity at 2.

2 / 3

Progressive Disclosure

It references real bundle scripts (generate-workflow.sh, discover-workflow.sh, etc.) and uses clear sections, but the CLI Reference and Examples duplicate inline content that could live in a single reference file, and script references are mentioned only in the overview rather than clearly signaled per topic.

2 / 3

Total

9

/

12

Passed

Description

72%

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 specific and distinctive, clearly conveying what the skill does with concrete action verbs. Its main weakness is the missing 'Use when...' trigger clause, which caps completeness and leaves trigger guidance implicit.

Suggestions

Add an explicit 'Use when...' clause, e.g. 'Use when chaining muapi.ai image, video, enhancement, or editing steps into automated pipelines.'

Include natural user-facing trigger terms like 'AI workflow', 'muapi workflow', or 'automate generation steps' alongside the domain vocabulary.

DimensionReasoningScore

Specificity

Lists multiple concrete actions — 'Build, run, and visualize multi-step AI generation workflows', 'translates natural language descriptions into connected node graphs', and 'chain image generation, video creation, enhancement, and editing into automated pipelines' — matching the top anchor.

3 / 3

Completeness

It clearly answers 'what does this do' but has no 'Use when...' clause or equivalent explicit trigger guidance, so per the rubric guidelines completeness is capped at 2.

2 / 3

Trigger Term Quality

Contains relevant terms (image generation, video creation, enhancement, editing, pipelines, node graphs) but lacks common user-facing variations like 'AI workflow', 'muapi', or 'automate generation' that a user would naturally say.

2 / 3

Distinctiveness Conflict Risk

The 'muapi.ai generation steps / node graphs' niche is specific and unlikely to conflict with other skills, with distinct triggers tied to multi-step generation pipelines.

3 / 3

Total

10

/

12

Passed

Validation

93%

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

Validation15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

15

/

16

Passed

Repository
SamurAIGPT/Generative-Media-Skills
Reviewed

Table of Contents

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