Name: api4ai
Rating: 64 (1 reviews)
Author: membranedev

api4ai

Api4ai integration. Manage Leads, Persons, Organizations, Deals, Projects, Pipelines and more. Use when the user wants to interact with Api4ai data.

Quality

76%

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Quality

Content

86%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 content is highly actionable with concrete executable commands and a clear connection-state workflow, well-organized in a single file. Minor verbosity in the introductory prose is the main weakness.

Dimension	Reasoning	Score
Conciseness	The body is mostly lean executable CLI commands with flags, but a few sections restate context Claude already knows (the Api4ai overview paragraph, the 'so you can focus on the integration logic rather than auth plumbing' aside).	4 / 5
Actionability	Concrete, copy-paste-ready membrane commands appear throughout (login, connection ensure/get, action list/run, request proxy) with exact flags, --json usage, and parameter examples covering the common cases.	5 / 5
Workflow Clarity	The connection flow is explicitly sequenced with state-based checkpoints (READY/BUILDING/CLIENT_ACTION_REQUIRED/CONFIGURATION_ERROR) and a poll loop, though recovery guidance for CONFIGURATION_ERROR is only briefly 'check the error field'.	4 / 5
Progressive Disclosure	A single self-contained file with well-organized sections and no nested or buried references; no bundle files are needed for this scope.	5 / 5
	Total	18 / 20 Passed

Description

66%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 names a distinct product and supplies an explicit 'Use when' clause, satisfying both what and when. It is weakened by a generic verb and entity list that do not reflect the actual image/video AI domain and by thin trigger-term variety.

Suggestions

Replace the generic 'Manage' with concrete Api4ai actions (e.g., 'Detect objects in images and videos, run analysis on media via API').

Align the entity list with Api4ai's real capabilities (image/video recognition) rather than CRM-style objects like Leads and Deals.

Add natural trigger phrases users would say, such as 'image recognition', 'object detection', or 'analyze an image'.

Dimension	Reasoning	Score
Specificity	Names the Api4ai domain and enumerates entities (Leads, Persons, Organizations, Deals, Projects, Pipelines), but the verb 'Manage' is generic and the listed entities do not match the actual image/video AI domain, so concrete actions remain minimal.	3 / 5
Completeness	A clear 'what' (Api4ai integration, manage listed entities) is paired with an explicit 'when' clause ('Use when the user wants to interact with Api4ai data'), though the trigger is somewhat generic.	4 / 5
Trigger Term Quality	Only the product name 'Api4ai' and 'Api4ai data' appear as triggers; common natural-language variations or synonyms a user would say are missing.	3 / 5
Distinctiveness Conflict Risk	Naming a specific branded product (Api4ai) gives it a clear niche with minimal overlap risk against other skills.	5 / 5
	Total	15 / 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/api4ai/SKILL.md
Commit: f484c82

Reviewed: 3 days ago

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