Name: flowiseai
Rating: 60 (1 reviews)
Author: membranedev

flowiseai

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

Quality

70%

Does it follow best practices?

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Securityby

Low

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tessl review fix ./skills/flowiseai/SKILL.md

Quality

Content

82%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 copy-paste-ready Membrane commands and a strong validation loop for connection setup. Its main weaknesses are inconsistent step numbering, a duplicated actions section, and a placeholder-like overview list.

Suggestions

Fix the step numbering: add a labeled "Step 1"/"1a" before "1b" and either label the referenced "Step 2" or remove the cross-reference.

Merge the redundant "Searching for actions" and "Popular actions" sections into a single action-discovery section.

Either flesh out the FlowiseAI Overview bullets (Chatflow/Version/API Key) with real guidance or remove them if they are placeholders.

Dimension	Reasoning	Score
Conciseness	The body is mostly efficient command examples, with only minor over-explanation such as the opening product blurb and "so you can focus on the integration logic rather than auth plumbing".	4 / 5
Actionability	It provides copy-paste-ready commands for install, login, connection setup, polling, action search/run, and proxy requests, plus a concrete flags table covering the common cases.	5 / 5
Workflow Clarity	The connection setup has an explicit validation/feedback loop via state polling (READY/BUILDING/CLIENT_ACTION_REQUIRED), but step numbering is inconsistent ("1b" with no "1a", "skip to Step 2" with no labeled Step 2) and the Popular actions section duplicates Searching for actions.	4 / 5
Progressive Disclosure	There are no bundle files and the body is organized into clear section headers with no nested references, but the sparse FlowiseAI Overview bullet list reads as a placeholder and the popular/searching sections overlap.	4 / 5
	Total	17 / 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 is third-person and supplies an explicit use-when trigger, but its capability verbs are generic and lack concrete actions. Trigger coverage leans heavily on the product name without synonyms or variations.

Suggestions

Replace generic verbs with concrete FlowiseAI actions, e.g. "Create and manage chatflows, versions, and API keys; run and monitor LLM flows."

Broaden trigger terms beyond the product name, e.g. "Use when the user mentions FlowiseAI, chatflows, LLM flow building, or visual AI agent design."

Tie the "when" clause to specific user intents (building, testing, deploying AI flows) rather than the vague "interact with FlowiseAI data".

Dimension	Reasoning	Score
Specificity	The description names the FlowiseAI domain but its actions ("Manage data, records, and automate workflows") are generic rather than concrete, matching the anchor for domain-named but minimal/generic actions.	2 / 5
Completeness	It states both a what ("Manage data, records, and automate workflows") and an explicit when ("Use when the user wants to interact with FlowiseAI data"), but the when could be more specific, fitting the both-present-but-could-be-sharper anchor.	4 / 5
Trigger Term Quality	"FlowiseAI", "data", "workflows", and "records" provide some relevant keywords, but coverage relies on the product name with no synonyms or common variations, matching the anchor for partial keyword coverage.	3 / 5
Distinctiveness Conflict Risk	The named FlowiseAI product gives a distinct trigger with minimal conflict risk, but the generic capability verbs (data, records, workflows) create minor overlap with other integration 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/flowiseai/SKILL.md
Commit: f484c82

Reviewed: 5 days ago

Table of Contents

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