tensorflow-savedmodel-creator
Tensorflow Savedmodel Creator - Auto-activating skill for ML Deployment. Triggers on: tensorflow savedmodel creator, tensorflow savedmodel creator Part of the ML Deployment skill category.
Install with Tessl CLI
npx tessl i github:jeremylongshore/claude-code-plugins-plus-skills --skill tensorflow-savedmodel-creatorOverall
score
19%
Does it follow best practices?
Validation for skill structure
Activation
7%This description is severely underdeveloped, essentially just a title with no substantive content. It fails to explain what actions the skill performs, provides no natural trigger terms users would say, and lacks any guidance on when Claude should use it. The auto-generated format with duplicate trigger terms suggests this is a placeholder rather than a thoughtfully crafted description.
Suggestions
Add specific actions the skill performs, e.g., 'Converts Keras/TensorFlow models to SavedModel format, configures serving signatures, optimizes for deployment'
Include a 'Use when...' clause with natural triggers like 'Use when exporting TensorFlow models, creating .pb files, preparing models for TF Serving, or deploying to production'
Add natural keyword variations users would say: 'save model', 'export model', 'tf serving', 'model deployment', 'protobuf', '.pb format'
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | The description only names the tool ('Tensorflow Savedmodel Creator') and category ('ML Deployment') but provides no concrete actions. It doesn't explain what the skill actually does - no verbs describing capabilities like 'converts models', 'exports weights', or 'serializes architectures'. | 1 / 3 |
Completeness | The description fails to answer 'what does this do' beyond the name, and has no 'Use when...' clause or equivalent guidance for when Claude should select this skill. Both the what and when are essentially missing. | 1 / 3 |
Trigger Term Quality | The trigger terms are just the skill name repeated twice ('tensorflow savedmodel creator, tensorflow savedmodel creator'). Missing natural user terms like 'save model', 'export tensorflow', 'savedmodel format', '.pb files', 'model serialization', or 'deploy tensorflow model'. | 1 / 3 |
Distinctiveness Conflict Risk | The TensorFlow SavedModel format is specific enough to distinguish from general ML skills, but without describing actual capabilities, it could conflict with other TensorFlow-related skills or general model export/deployment skills. | 2 / 3 |
Total | 5 / 12 Passed |
Implementation
0%This skill content is entirely generic boilerplate with no actual substance about TensorFlow SavedModel creation. It contains no code examples, no specific commands (like tf.saved_model.save()), no workflow for exporting models, and no practical guidance. The content could apply to virtually any topic by swapping the keyword.
Suggestions
Add executable Python code showing how to create a SavedModel using tf.saved_model.save() with a concrete model example
Include a clear workflow: 1) Define/load model, 2) Define signatures, 3) Save with tf.saved_model.save(), 4) Validate with saved_model_cli
Provide specific commands for validation: 'saved_model_cli show --dir /path/to/model --all' to verify the exported model
Remove all generic boilerplate sections (Purpose, When to Use, Example Triggers) and replace with actionable content about serving signatures, input/output specifications, and common export patterns
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is padded with generic boilerplate that explains nothing specific about TensorFlow SavedModel creation. Every section describes what the skill does abstractly rather than providing actual guidance Claude could use. | 1 / 3 |
Actionability | No concrete code, commands, or executable guidance is provided. The content only describes capabilities in vague terms like 'provides step-by-step guidance' without actually providing any steps, code examples, or specific instructions. | 1 / 3 |
Workflow Clarity | No workflow is defined. There are no steps, no sequence, and no validation checkpoints for creating TensorFlow SavedModels. The skill claims to provide 'step-by-step guidance' but includes none. | 1 / 3 |
Progressive Disclosure | The content is a monolithic block of generic placeholder text with no references to detailed materials, no links to examples, and no structured navigation to additional resources about SavedModel creation. | 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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