torchserve-config-generator
Torchserve Config Generator - Auto-activating skill for ML Deployment. Triggers on: torchserve config generator, torchserve config generator Part of the ML Deployment skill category.
Install with Tessl CLI
npx tessl i github:jeremylongshore/claude-code-plugins-plus-skills --skill torchserve-config-generatorOverall
score
19%
Does it follow best practices?
Validation for skill structure
Activation
7%This description is severely underdeveloped, essentially just restating the skill name without explaining capabilities or use cases. It lacks concrete actions, meaningful trigger terms, and explicit guidance on when to use it. The redundant trigger terms and boilerplate category mention provide no useful information for skill selection.
Suggestions
Add specific actions the skill performs, e.g., 'Generates TorchServe configuration files including model-config.yaml, config.properties, and handler definitions for deploying PyTorch models'
Include a 'Use when...' clause with natural trigger scenarios, e.g., 'Use when deploying PyTorch models to production, setting up model serving infrastructure, or configuring inference endpoints'
Add varied trigger terms users might naturally say: 'deploy pytorch model', 'model serving', 'inference server', 'torch serve setup', 'MAR file', 'model archive'
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | The description only names the tool ('Torchserve Config Generator') without describing any concrete actions. It doesn't explain what configurations it generates, what parameters it handles, or what outputs it produces. | 1 / 3 |
Completeness | The description fails to answer 'what does this do' beyond the name, and has no explicit 'Use when...' clause. The trigger list is not a substitute for explaining when Claude should select this skill. | 1 / 3 |
Trigger Term Quality | The trigger terms are redundant (lists 'torchserve config generator' twice) and overly specific. Missing natural variations users might say like 'model serving config', 'deploy pytorch model', 'inference server setup', or 'torch serve'. | 1 / 3 |
Distinctiveness Conflict Risk | The mention of 'torchserve' and 'ML Deployment' provides some specificity to the domain, but without describing actual capabilities, it could overlap with other ML deployment or configuration generation skills. | 2 / 3 |
Total | 5 / 12 Passed |
Implementation
0%This skill is essentially a placeholder template with no actual content about TorchServe configuration generation. It contains only generic meta-descriptions of what a skill should do without any actionable information, executable code, configuration examples, or specific guidance for generating TorchServe configs.
Suggestions
Add concrete TorchServe config.properties examples showing actual configuration parameters (model_store, inference_address, management_address, etc.)
Include executable Python code or CLI commands for generating and validating TorchServe configurations
Provide a clear workflow: 1) Define model requirements, 2) Generate config, 3) Validate config, 4) Deploy with specific validation steps
Remove all generic boilerplate ('provides automated assistance', 'follows best practices') and replace with actual TorchServe-specific guidance
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is padded with generic boilerplate that explains nothing Claude doesn't already know. Phrases like 'provides automated assistance' and 'follows industry best practices' are meaningless filler with no actual information about TorchServe configuration. | 1 / 3 |
Actionability | There is zero concrete guidance - no code examples, no configuration snippets, no specific commands, no actual TorchServe config parameters or file formats. The skill describes what it does rather than instructing how to do anything. | 1 / 3 |
Workflow Clarity | No workflow is defined at all. There are no steps, no sequence, no validation checkpoints. The 'Capabilities' section mentions 'step-by-step guidance' but provides none. | 1 / 3 |
Progressive Disclosure | The content is a monolithic block of generic text with no structure pointing to detailed materials, no references to configuration examples, schema documentation, or related files. | 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
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