Name: aivoov
Rating: 55.2 (1 reviews)
Author: membranedev

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aivoov

AiVOOV integration. Manage data, records, and automate workflows. Use when the user wants to interact with AiVOOV data.

Quality

62%

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Quality

Content

67%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 concrete CLI commands and a state-driven connection workflow, weakened mainly by a speculative intro paragraph and an incomplete actions table. Structure and sequencing are solid with only minor organizational gaps.

Suggestions

Delete or replace the hedging intro ("likely provides... probably used by...") with a one-line factual description of AiVOOV's purpose.

Fill the empty Description cells in the Popular actions table so the action list is self-contained.

Reconcile the "skip to Step 2" reference and relabel "1b" with an explicit Step 1 / Step 2 structure so the workflow sequence is unambiguous.

Dimension	Reasoning	Score
Conciseness	Mostly efficient command examples, but the opening speculation ("AiVOOV is a platform that likely provides... It's probably used by...") is unnecessary hedging Claude does not need, and the empty "Popular actions" descriptions add padding, fitting the mostly-efficient-but-could-be-tightened anchor.	3 / 5
Actionability	Concrete executable commands appear throughout (install, login, connection ensure with --wait polling, action run with --input JSON, request proxy with a full flag table), with only minor gaps such as unfilled placeholders and empty table descriptions.	4 / 5
Workflow Clarity	The connection flow is sequenced with state-based checkpoints (READY / BUILDING / CLIENT_ACTION_REQUIRED / CONFIGURATION_ERROR) and a re-poll feedback loop, but the orphaned "skip to Step 2" and a "1b" heading without a "1a"/"Step 1" introduce minor structural gaps.	4 / 5
Progressive Disclosure	The body is well-sectioned with clear headers and an external docs link, with content appropriately inline for a single-file skill; the only gaps are that the proxy-options table and agent-types list could live in separate reference files.	4 / 5
	Total	15 / 20 Passed

Description

57%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 answers both what and when with a clear brand anchor, but its capability verbs are generic and it offers few natural trigger terms beyond the product name. Tightening the action list and adding concrete trigger phrases would lift the weaker dimensions.

Suggestions

Replace generic verbs ("Manage data, records, and automate workflows") with concrete AiVOOV actions like "generate voiceovers, list voices, and convert text to speech".

Expand the trigger clause with natural synonyms users would say, e.g. "Use when the user wants text-to-speech, voiceover, or dubbing via AiVOOV".

Add file-format or feature triggers (e.g. audio output formats) to improve distinctiveness against general data-automation skills.

Dimension	Reasoning	Score
Specificity	The phrase "Manage data, records, and automate workflows" names the domain but the actions are minimal and generic ("manage", "automate") rather than concrete operations, matching the score-2 anchor of naming the domain with generic actions.	2 / 5
Completeness	Both a "what" (AiVOOV integration; manage data, records, automate workflows) and an explicit "when" ("Use when the user wants to interact with AiVOOV data") are present, though the "when" could be more specific, matching the both-present-but-could-be-sharper anchor.	4 / 5
Trigger Term Quality	"Use when the user wants to interact with AiVOOV data" supplies the brand keyword and a "data" trigger, but lacks common variations or synonyms beyond the brand name, fitting the some-relevant-keywords anchor.	3 / 5
Distinctiveness Conflict Risk	The distinct brand name "AiVOOV" gives it a clear niche and brand-specific trigger, but the generic "manage data, records, automate workflows" phrasing creates minor overlap risk with other data-management skills.	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: membranedev/application-skills
Path: skills/aivoov/SKILL.md
Commit: f484c82

Reviewed: 3 days ago

Table of Contents

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