Name: melissa-data
Rating: 49.6 (1 reviews)
Author: membranedev

melissa-data

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

Quality

54%

Does it follow best practices?

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Securityby

Low

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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 a well-structured, actionable Membrane CLI integration guide with a clear state-machine workflow and feedback loops. Its main weakness is mild over-explanation and editorializing that could be trimmed for token efficiency.

Suggestions

Trim editorializing such as "so you can focus on the integration logic rather than auth plumbing" and "This is the fastest way to get a connection" to keep the context lean.

Remove the background paragraph about who uses Melissa Data ("Developers and businesses use it to improve data quality...") since it does not guide action.

Consolidate the overlapping 'Searching for actions' and 'Popular actions' sections to avoid redundant discovery instructions.

Dimension	Reasoning	Score
Conciseness	The body is mostly efficient CLI commands, but includes unnecessary editorializing Claude does not need ("so you can focus on the integration logic rather than auth plumbing", "This is the fastest way", and background on who uses Melissa Data), fitting the 'mostly efficient but some unnecessary explanation' anchor.	3 / 5
Actionability	It provides concrete, copy-paste-ready commands throughout (install, login, connection ensure, action run, proxy flags) with only minor gaps such as left-abstract placeholders, matching the 'mostly executable guidance with minor gaps' anchor.	4 / 5
Workflow Clarity	The install → login → connect → poll → search → run sequence is clear with explicit state-machine checkpoints and a poll/feedback loop for CLIENT_ACTION_REQUIRED and error states, matching the 'clear sequence with most checkpoints' anchor.	4 / 5
Progressive Disclosure	Content is well-organized under clear headers in a single file with no nested references; structure is good with only minor organization gaps (e.g. the 'Popular actions' section partially overlaps with 'Searching for actions'), fitting the 4 anchor.	4 / 5
	Total	15 / 20 Passed

Description

41%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 correctly names the Melissa Data niche and includes an explicit 'Use when' trigger, but its action verbs and trigger terms are generic rather than concrete. Specificity and trigger-term coverage are the main weaknesses.

Suggestions

Replace generic verbs with concrete capabilities, e.g. "Verify addresses, enrich records, and verify identity via Melissa Data."

Add natural trigger keywords users would say, such as "address verification", "data enrichment", "identity verification", or "clean customer databases".

Tighten the 'Use when' clause to specific intents, e.g. "Use when the user wants to verify addresses, enrich contact data, or validate identity."

Dimension	Reasoning	Score
Specificity	Names the Melissa Data domain but the listed actions ("Manage data, records, and automate workflows") are minimal and generic, fitting the 'names the domain but actions are minimal or generic' anchor rather than the 1-2 concrete actions of score 3.	2 / 5
Completeness	It has a clear 'what' (manage data, records, automate workflows) and an explicit 'Use when' clause, but the 'when' is generic and the 'what' is vague, so it sits at the 3 anchor (clear what, weak when) rather than the more explicit 4.	3 / 5
Trigger Term Quality	Only the brand term "Melissa Data" repeats alongside the generic word "data"; it is missing the natural phrases users actually say (address verification, data enrichment, identity verification, cleaning databases), matching the 'one or two generic keywords' anchor.	2 / 5
Distinctiveness Conflict Risk	The brand-specific niche ("Melissa Data integration") gives a distinct trigger with only minor overlap risk against other data-quality skills, matching the 'mostly distinct; minor overlap risk' anchor.	4 / 5
	Total	11 / 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/melissa-data/SKILL.md
Commit: f484c82

Reviewed: 6 days ago

Table of Contents

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