Name: lighton
Rating: 56.8 (1 reviews)
Author: membranedev

lighton

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

Quality

65%

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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 solid, command-driven integration guide with executable examples, a clear multi-step workflow, and explicit state-handling checkpoints. Its weakest point is conciseness: a marketing-flavored intro and an unexplained overview list pad the otherwise lean instructions.

Suggestions

Cut the introductory marketing sentence about researchers/companies and complex ML models; keep only the one-line platform description and the docs link.

Either expand the bare "LightOn Overview" list (Notebook/Cell/Terminal) into useful guidance or remove it so it is not unexplained padding.

Fix the broken "skip to Step 2" cross-reference by labeling the next phase (e.g., "## 2. Search for actions") so the workflow sequence is internally consistent.

Dimension	Reasoning	Score
Conciseness	The body is mostly efficient command examples, but the opening marketing paragraph ("used by researchers and companies needing accelerated computation for complex machine learning models") and the sparse, unexplained "LightOn Overview" list (Notebook/Cell/Terminal) add padding Claude does not need, matching the mostly-efficient-with-some-unnecessary-explanation anchor.	3 / 5
Actionability	It provides concrete executable commands throughout (npm install, membrane login, connection ensure/get, action list/run, request) plus a flags table, with only minor gaps from placeholders like CONNECTION_ID and QUERY, matching the mostly-executable-guidance anchor.	4 / 5
Workflow Clarity	The install→authenticate→connect→wait→search→run flow is clearly sequenced with state-machine checkpoints (READY/BUILDING/CLIENT_ACTION_REQUIRED) and a poll-again feedback loop; the only gap is a "skip to Step 2" reference to a non-existent Step 2, matching clear sequence with minor validation gaps.	4 / 5
Progressive Disclosure	The skill is a single well-organized file with clear section headers and no nested or buried references (no bundle files exist), matching the good-structure anchor with minor organization gaps.	4 / 5
	Total	15 / 20 Passed

Description

62%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 competent: it states a clear what, an explicit Use-when trigger, and ties to a named platform for distinctiveness. Its main weakness is generic action verbs and thin trigger-term coverage that limit specificity and trigger quality to the midpoint.

Suggestions

Replace generic verbs ("Manage data, records") with concrete LightOn-specific operations (e.g., "query records, create and update entries, run automated workflows") to lift specificity.

Expand the trigger clause with natural variations a user might say, e.g. "Use when the user wants to query, create, or update LightOn records or run LightOn workflows."

Add at least one concrete trigger phrase beyond "interact with LightOn data" to push completeness toward an explicit, varied when-clause.

Dimension	Reasoning	Score
Specificity	"Manage data, records, and automate workflows" names the LightOn domain with 2-3 actions, but the verbs are generic/abstract rather than concrete operations like extract, fill, or merge, matching the anchor for naming domain plus a couple of actions without comprehensive coverage.	3 / 5
Completeness	It states both a "what" (Manage data, records, and automate workflows) and an explicit "Use when..." trigger, but the "when" is generic rather than enumerating concrete trigger phrases, matching the anchor for having both with an improvable when.	4 / 5
Trigger Term Quality	The trigger "Use when the user wants to interact with LightOn data" includes relevant keywords (LightOn, data) but offers no synonyms, variations, or file extensions, fitting the anchor for some relevant keywords missing common variations.	3 / 5
Distinctiveness Conflict Risk	Naming the specific LightOn platform gives it a clear niche with only minor overlap risk against closely related data-integration skills, matching the mostly-distinct anchor.	4 / 5
	Total	14 / 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/lighton/SKILL.md
Commit: f484c82

Reviewed: 6 days ago

Table of Contents

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