Name: altoviz
Rating: 53.6 (1 reviews)
Author: membranedev

altoviz

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

Quality

60%

Does it follow best practices?

Run evals on this skill

Adds up to 20 points to the overall score

View guide

Securityby

Passed

No findings from the security scan

Fix and improve this skill with Tessl

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

Quality

Content

63%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 delivers highly actionable, executable CLI guidance with a well-sequenced connection state machine, but it is held back by padded introductory prose and a low-value actions table that would be better split into a reference file.

Suggestions

Move the 20-row popular-actions table and the proxy flag reference into a separate REFERENCE.md, leaving SKILL.md as a concise overview with a clearly signaled link.

Remove the generic platform intro paragraph and the placeholder line "Use action names and parameters as needed." to tighten token use.

Populate or drop the "No description" cells in the actions table, since 20 identical placeholders add bulk without guidance value.

Dimension	Reasoning	Score
Conciseness	Mostly efficient with copy-ready command blocks, but it includes unnecessary padding such as the generic intro "Altoviz is a data visualization and analytics platform...", the vague line "Use action names and parameters as needed.", and a 20-row actions table where every description is "No description", fitting 'mostly efficient but includes some unnecessary explanation'.	3 / 5
Actionability	It provides concrete, executable commands throughout (npm install, membrane login, connection ensure, action list/run, request with flag tables), copy-paste ready with minor gaps such as unexpanded CONNECTION_ID placeholders, matching 'mostly executable guidance; concrete commands with minor gaps'.	4 / 5
Workflow Clarity	The connect-to-ready flow is sequenced with an explicit state machine (READY/BUILDING/CLIENT_ACTION_REQUIRED/CONFIGURATION_ERROR) and a poll-until-ready feedback loop, giving clear checkpoints with only minor gaps in the surrounding step numbering, matching 'clear sequence with most checkpoints present'.	4 / 5
Progressive Disclosure	It is a single ~160-line file with no external reference files; section headers give some structure, but bulk content like the 20-row actions table and flag reference arguably belong in a separate file and no one-level-deep references are signaled, matching 'some structure but could be better organized; content that should be separate is inline'.	3 / 5
	Total	14 / 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 correctly pairs a what-statement with an explicit 'Use when' trigger and leverages a distinctive brand name, but its action verbs are generic and it lacks concrete capability examples or richer trigger phrasing.

Suggestions

Replace generic verbs with concrete Altoviz capabilities, e.g. "List and create invoices, quotes, products, customers, and suppliers".

Expand the trigger clause with concrete phrases users would say, e.g. "Use when the user wants to manage Altoviz invoices, quotes, customers, or products".

Drop the redundant "Altoviz integration." opener since the name and actions already convey the domain, tightening token use.

Dimension	Reasoning	Score
Specificity	"Manage data, records, and automate workflows" names the Altoviz domain but relies on generic verbs ("manage") rather than concrete actions like list/create/update invoices or customers, matching the 'names the domain but actions are minimal or generic' anchor.	2 / 5
Completeness	Both halves are present — what ("Manage data, records, and automate workflows") and when ("Use when the user wants to interact with Altoviz data"), but the trigger clause is generic rather than listing concrete trigger phrases, matching 'has both what and when; when could be more explicit or specific'.	4 / 5
Trigger Term Quality	It surfaces the natural keyword "Altoviz" plus "data" and "records", but offers no synonyms or variations a user might say beyond the brand name, fitting 'some relevant keywords but missing common variations or synonyms'.	3 / 5
Distinctiveness Conflict Risk	Naming the specific app "Altoviz" as the trigger gives a clear niche with low conflict risk, but the generic "manage data, records" verbs introduce minor overlap with other data skills, so it sits at 'mostly distinct; minor overlap risk'.	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/altoviz/SKILL.md
Commit: f484c82

Reviewed: 3 days ago

Table of Contents

Discovery Implementation Validation

Is this your skill?

If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.