mlflow-tracking-setup
Mlflow Tracking Setup - Auto-activating skill for ML Training. Triggers on: mlflow tracking setup, mlflow tracking setup Part of the ML Training skill category.
Overall
score
28%
Does it follow best practices?
Validation for skill structure
Install with Tessl CLI
npx tessl i github:jeremylongshore/claude-code-plugins-plus-skills --skill mlflow-tracking-setupActivation
22%This description is severely underdeveloped, essentially just restating the skill name without explaining capabilities or providing meaningful usage guidance. It lacks concrete actions, comprehensive trigger terms, and explicit 'when to use' instructions that would help Claude select this skill appropriately from a larger skill library.
Suggestions
Add specific actions the skill performs, e.g., 'Configures MLflow tracking servers, sets up experiment logging, initializes artifact storage, and manages run parameters for ML experiments.'
Include a 'Use when...' clause with natural trigger scenarios: 'Use when setting up experiment tracking, logging ML metrics, configuring MLflow server, or when user mentions experiment runs, model artifacts, or hyperparameter logging.'
Expand trigger terms to include variations users might naturally say: 'mlflow', 'experiment tracking', 'log metrics', 'model registry', 'artifact logging', 'ML experiment management'.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | The description only mentions 'mlflow tracking setup' without describing any concrete actions. It doesn't explain what the skill actually does - no verbs describing capabilities like 'configure', 'initialize', 'log experiments', etc. | 1 / 3 |
Completeness | The description fails to answer 'what does this do' beyond the name itself, and the 'when' guidance is extremely limited to just the exact phrase 'mlflow tracking setup'. There's no explicit 'Use when...' clause with meaningful trigger scenarios. | 1 / 3 |
Trigger Term Quality | Includes 'mlflow tracking setup' as a trigger term which is relevant, but the trigger list is redundant (same term twice) and misses common variations users might say like 'experiment tracking', 'log metrics', 'MLflow experiments', or 'model logging'. | 2 / 3 |
Distinctiveness Conflict Risk | The mention of 'mlflow' provides some specificity that distinguishes it from generic ML skills, but 'ML Training' category overlap and lack of specific use cases could cause confusion with other ML-related skills. | 2 / 3 |
Total | 6 / 12 Passed |
Implementation
7%This skill content is a generic template with no actual MLflow-specific guidance. It describes capabilities in abstract terms but provides no concrete code, commands, configuration examples, or workflows for setting up MLflow tracking. The content fails to teach Claude anything it doesn't already know.
Suggestions
Add executable Python code showing MLflow tracking setup (e.g., `mlflow.set_tracking_uri()`, `mlflow.start_run()`, logging parameters/metrics)
Include a concrete workflow: 1) Configure tracking URI, 2) Set experiment, 3) Start run, 4) Log params/metrics/artifacts, 5) End run
Remove generic boilerplate sections ('Capabilities', 'Example Triggers') and replace with actual configuration examples and common patterns
Add specific guidance for common scenarios: local tracking, remote server setup, artifact storage configuration
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is padded with generic boilerplate that explains nothing specific about MLflow tracking setup. Phrases like 'provides automated assistance' and 'follows industry best practices' are filler that Claude doesn't need. | 1 / 3 |
Actionability | No concrete code, commands, or specific instructions for setting up MLflow tracking. The content describes what the skill does abstractly but provides zero executable guidance. | 1 / 3 |
Workflow Clarity | No steps, sequence, or workflow provided. Claims to provide 'step-by-step guidance' but includes none. No validation checkpoints or actual process described. | 1 / 3 |
Progressive Disclosure | The content is organized into clear sections with headers, but there are no references to detailed documentation, examples, or related files. The structure exists but contains no substantive content to disclose. | 2 / 3 |
Total | 5 / 12 Passed |
Validation
69%Validation — 11 / 16 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
description_trigger_hint | Description may be missing an explicit 'when to use' trigger hint (e.g., 'Use when...') | Warning |
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 |
body_steps | No step-by-step structure detected (no ordered list); consider adding a simple workflow | Warning |
Total | 11 / 16 Passed | |
Reviewed
Table of Contents
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