tracking-model-versions

tessl i github:jeremylongshore/claude-code-plugins-plus-skills --skill tracking-model-versions

Build this skill enables AI assistant to track and manage ai/ml model versions using the model-versioning-tracker plugin. it should be used when the user asks to manage model versions, track model lineage, log model performance, or implement version control f... Use when appropriate context detected. Trigger with relevant phrases based on skill purpose.

32%

Overall

Validation — 81%

Implementation — 7%

Activation — 33%

SKILL.md

Review

Evals

Validation

81%

Warnings & errors only

Criteria	Description	Result
allowed_tools_field	'allowed-tools' contains unusual tool name(s)	Warning
metadata_version	'metadata' field is not a dictionary	Warning
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	13 / 16 Passed

Implementation

This skill is essentially a template with placeholder content that provides no actionable guidance for using the model-versioning-tracker plugin. It lacks any concrete code examples, specific API calls, or actual commands. The content is padded with generic statements and boilerplate that Claude already knows, wasting tokens without providing value.

Suggestions

Add executable code examples showing actual API calls to the model-versioning-tracker plugin (e.g., specific function calls, CLI commands, or SDK usage)

Remove redundant content like the duplicate overview statement and generic sections (Error Handling, Prerequisites, Instructions) that provide no specific information

Replace abstract example descriptions with concrete input/output pairs showing actual code and expected responses

Specify the actual dependencies, configuration requirements, and plugin interface details needed to use this skill

Dimension	Reasoning	Score
Conciseness	Extremely verbose with redundant sections (Overview repeats itself), explains obvious concepts Claude knows (what version control is, what error handling means), and includes generic boilerplate that adds no value ('This skill provides automated assistance for model versioning tracker tasks' appears twice).	1 / 3
Actionability	No concrete code, commands, or executable examples provided. Examples describe what 'the skill will do' abstractly rather than showing actual code to interact with the model-versioning-tracker plugin. Prerequisites mention 'required dependencies' without naming them.	1 / 3
Workflow Clarity	The 'How It Works' section is vague ('Generate Code', 'Execute Task') without showing actual steps. No validation checkpoints, no specific commands, and the Instructions section is completely generic boilerplate that could apply to any skill.	1 / 3
Progressive Disclosure	Content is organized into sections with headers, but everything is in one file with no references to external documentation. The structure exists but contains mostly filler content that doesn't warrant the organization.	2 / 3
	Total	5 / 12 Passed

Activation

33%

This description suffers from a truncated capability list and completely generic, unhelpful trigger guidance that defeats the purpose of the 'Use when' clause. While it identifies a specific domain (AI/ML model versioning), the boilerplate language provides no actionable selection criteria for Claude to distinguish this skill from others.

Suggestions

Replace the generic 'Use when appropriate context detected' with specific triggers like 'Use when the user mentions model versioning, experiment tracking, model registry, ML model lineage, or comparing model performance across versions'

Complete the truncated capability list and use concrete action verbs in third person (e.g., 'Tracks model versions, logs performance metrics, manages model lineage, compares experiments')

Add natural user phrases and file/tool references users might mention (e.g., 'MLflow', 'model checkpoints', '.pkl files', 'model artifacts')

Dimension	Reasoning	Score
Specificity	Names the domain (AI/ML model versioning) and lists some actions (track model versions, track model lineage, log model performance, implement version control), but the description is truncated and uses vague language like 'enables AI assistant' rather than concrete action verbs.	2 / 3
Completeness	The 'what' is partially present but truncated. The 'when' clause is completely generic boilerplate ('Use when appropriate context detected. Trigger with relevant phrases based on skill purpose') that provides no actual guidance on when to use this skill.	1 / 3
Trigger Term Quality	Contains some relevant keywords like 'model versions', 'model lineage', 'model performance', 'version control', but the generic 'Trigger with relevant phrases based on skill purpose' adds no value and the description lacks natural variations users might say (e.g., 'ML models', 'experiment tracking', 'model registry').	2 / 3
Distinctiveness Conflict Risk	The AI/ML model versioning domain is somewhat specific, but the truncated description and generic trigger guidance could cause overlap with general version control skills or other ML-related skills.	2 / 3
	Total	7 / 12 Passed

Reviewed

17 days ago

Table of Contents

Validation Implementation Activation

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