optuna-study-creator
Optuna Study Creator - Auto-activating skill for ML Training. Triggers on: optuna study creator, optuna study creator Part of the ML Training skill category.
Install with Tessl CLI
npx tessl i github:jeremylongshore/claude-code-plugins-plus-skills --skill optuna-study-creatorOverall
score
19%
Does it follow best practices?
Validation for skill structure
Activation
7%This description is severely underdeveloped, essentially just a title with redundant trigger terms. It provides no information about what the skill actually does with Optuna, what specific capabilities it offers, or when Claude should select it over other ML-related skills. The auto-generated format adds no value for skill selection.
Suggestions
Add specific capabilities: describe concrete actions like 'Creates Optuna studies for hyperparameter optimization, defines search spaces, configures samplers and pruners, and analyzes optimization results'
Include a 'Use when...' clause with natural trigger scenarios: 'Use when the user wants to tune hyperparameters, optimize model performance, run parameter searches, or mentions Optuna, HPO, or bayesian optimization'
Remove redundant trigger terms and expand to include natural variations users would actually say: 'hyperparameter tuning', 'optimize parameters', 'model optimization', 'trial-based search'
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | The description only names the tool ('Optuna Study Creator') and category ('ML Training') without describing any concrete actions. No specific capabilities like 'create optimization studies', 'define hyperparameter search spaces', or 'configure pruning strategies' are mentioned. | 1 / 3 |
Completeness | The description fails to answer 'what does this do' beyond the name, and the 'when' guidance is just a repetitive trigger phrase rather than meaningful usage context. No 'Use when...' clause with explicit scenarios. | 1 / 3 |
Trigger Term Quality | The trigger terms are redundant ('optuna study creator' listed twice) and overly specific. Missing natural variations users would say like 'hyperparameter tuning', 'optimize model', 'parameter search', 'HPO', or 'bayesian optimization'. | 1 / 3 |
Distinctiveness Conflict Risk | The mention of 'Optuna' specifically does provide some distinctiveness from generic ML skills, but 'ML Training' is broad and could overlap with other training-related skills. The lack of specific use cases increases conflict risk. | 2 / 3 |
Total | 5 / 12 Passed |
Implementation
0%This skill content is a generic template with no actual substance about Optuna study creation. It contains only meta-descriptions of what a skill should do rather than actionable instructions, code examples, or specific guidance for creating and configuring Optuna studies for hyperparameter optimization.
Suggestions
Add executable Python code showing how to create an Optuna study with `optuna.create_study()`, including sampler and pruner configuration
Include a concrete example of defining an objective function with trial.suggest_* methods for common hyperparameters
Provide a clear workflow: 1) Define objective function, 2) Create study with storage, 3) Run optimization, 4) Retrieve best parameters
Remove all generic boilerplate ('provides automated assistance', 'follows best practices') and replace with specific Optuna patterns and configurations
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is padded with generic boilerplate that explains nothing specific about Optuna study creation. 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 guidance for creating Optuna studies. The content describes what the skill does abstractly but provides zero executable instructions or examples. | 1 / 3 |
Workflow Clarity | No workflow is defined. There are no steps for creating an Optuna study, no validation checkpoints, and no sequence of operations. 'Provides step-by-step guidance' is claimed but not delivered. | 1 / 3 |
Progressive Disclosure | No structure beyond generic headings. No references to detailed documentation, no examples file, no API reference. The content is a shallow placeholder with no depth or navigation to additional resources. | 1 / 3 |
Total | 4 / 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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