Name: plate-recognizer
Rating: 55.2 (1 reviews)
Author: membranedev

plate-recognizer

Plate Recognizer integration. Manage Vehicles, Cameras, Regions, Users, Alerts. Use when the user wants to interact with Plate Recognizer data.

Quality

62%

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/plate-recognizer/SKILL.md

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, executable CLI integration guide with concrete commands and a well-structured connection-state workflow including feedback loops. It loses points mainly on conciseness (several padded passages) and could benefit from splitting dense reference material into bundle files.

Suggestions

Trim padded prose: remove the marketecture overview paragraph, the "auth plumbing" aside, and the filler line "Use action names and parameters as needed.".

Fix the dangling navigation — either define a numbered "Step 2" heading or reword "skip to Step 2" to reference a real section (e.g. "Searching for actions").

Move the proxy flags table and the full connection state-machine reference into a separate reference file, keeping SKILL.md as a lean overview with a one-level-deep pointer.

Dimension	Reasoning	Score
Conciseness	Mostly efficient with concrete commands, but several padded passages could be trimmed: the product overview paragraph ("used by developers and businesses...Common use cases include parking management, security, and traffic monitoring"), the "auth plumbing" aside, "This is the fastest way to get a connection", and the bare filler line "Use action names and parameters as needed."	3 / 5
Actionability	Provides concrete, copy-paste-ready CLI commands throughout (login, connection ensure, action list/run, request) plus a flags table, with only minor gaps — placeholder substitution (CONNECTION_ID, QUERY) is required and the "Popular actions" section is thin ("discover available actions" without concrete examples).	4 / 5
Workflow Clarity	A clear install → authenticate → connect → search → run sequence exists, and the connection state machine (READY/BUILDING/CLIENT_ACTION_REQUIRED/CONFIGURATION_ERROR) includes explicit polling feedback loops. Minor gaps: the dangling "skip to Step 2" reference has no matching Step 2 heading, and there is no output-validation guidance for action runs.	4 / 5
Progressive Disclosure	Well-organized into clearly labeled sections with no nested references (single ~140-line file; no bundle files exist), but all content is inlined — the detailed connection state machine and proxy flags table could arguably live in separate reference files given the file exceeds the 50-line simple-skill threshold.	4 / 5
	Total	15 / 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 clearly names the product and the entities it manages, and includes an explicit "Use when" clause, so it answers both what and when. Its main weakness is a single generic action verb ("Manage") and the absence of the core "license plate"/"ALPR" trigger terms users would naturally say.

Suggestions

Replace the single generic verb "Manage" with concrete actions per entity, e.g. "Register Vehicles, configure Cameras, define Regions, invite Users, and review Alerts".

Add the natural trigger terms users actually say — "license plate recognition", "ALPR", "LPR", "parking" — to the "Use when" clause.

Tighten the "when" clause to concrete triggers: "Use when the user wants to manage license plate recognition data, vehicles, cameras, regions, users, or alerts in Plate Recognizer."

Dimension	Reasoning	Score
Specificity	Names the domain and five concrete entities ("Vehicles, Cameras, Regions, Users, Alerts"), but uses a single generic verb ("Manage"), so the actions themselves are minimal rather than varied.	2 / 5
Completeness	Both "what" ("Manage Vehicles, Cameras, Regions, Users, Alerts") and "when" ("Use when the user wants to interact with Plate Recognizer data") are present, but the "when" clause is somewhat generic and circular rather than listing concrete triggers.	4 / 5
Trigger Term Quality	The entity nouns (Vehicles, Cameras, Alerts, Users, Regions) are natural terms users would say, but the description misses the core synonyms users most commonly use ("license plate", "ALPR", "LPR").	3 / 5
Distinctiveness Conflict Risk	Tied to a named product ("Plate Recognizer integration") giving it a clear niche, but the broad "interact with Plate Recognizer data" trigger and generic entity names create minor overlap risk with other vehicle/camera management 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/plate-recognizer/SKILL.md
Commit: f484c82

Reviewed: 5 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.