triton-inference-config
Triton Inference Config - Auto-activating skill for ML Deployment. Triggers on: triton inference config, triton inference config Part of the ML Deployment skill category.
41
Quality
11%
Does it follow best practices?
Impact
98%
0.98xAverage score across 3 eval scenarios
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./planned-skills/generated/08-ml-deployment/triton-inference-config/SKILL.mdQuality
Discovery
22%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
This description is severely underdeveloped, essentially serving as a label rather than a functional description. It names the skill and category but provides no information about what actions it performs or specific scenarios when it should be selected. The duplicate trigger term suggests incomplete editing.
Suggestions
Add specific actions the skill performs, e.g., 'Generates Triton Inference Server configuration files, defines model repositories, configures batching and instance groups.'
Expand trigger terms to include natural variations: 'triton server', 'model serving config', 'inference server setup', 'config.pbtxt', 'model repository'.
Add a clear 'Use when...' clause describing scenarios: 'Use when deploying ML models to Triton Inference Server, configuring model repositories, or setting up inference endpoints.'
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | The description only names 'Triton Inference Config' and 'ML Deployment' without describing any concrete actions. There are no verbs indicating what the skill actually does (e.g., generate, configure, validate). | 1 / 3 |
Completeness | The description fails to answer 'what does this do' beyond naming itself, and while it has a 'Triggers on' clause, it doesn't explain when Claude should use it in terms of user needs or scenarios. The 'what' is essentially missing. | 1 / 3 |
Trigger Term Quality | Includes 'triton inference config' as a trigger term (duplicated), which is a relevant technical term users might say. However, it lacks natural variations like 'model serving', 'inference server', 'triton server', 'model deployment config', or file extensions. | 2 / 3 |
Distinctiveness Conflict Risk | The mention of 'Triton Inference' provides some specificity to NVIDIA Triton Inference Server, but 'ML Deployment' is broad and could overlap with other deployment-related skills. The lack of specific actions makes it harder to distinguish. | 2 / 3 |
Total | 6 / 12 Passed |
Implementation
0%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This skill is a placeholder template with no actual Triton Inference Server content. It contains only meta-descriptions of what a skill should do without any concrete configuration examples, pbtxt syntax, model repository structure, or deployment commands. The skill provides zero value for someone actually trying to configure Triton.
Suggestions
Add concrete config.pbtxt examples showing model configuration with input/output tensors, batching settings, and instance groups
Include the model repository directory structure and required files (config.pbtxt, model versions)
Provide executable commands for starting Triton server and validating model loading (e.g., `tritonserver --model-repository=/models`)
Add a workflow for creating, validating, and deploying a model configuration with explicit validation checkpoints
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is entirely boilerplate with no actual Triton-specific information. It explains what the skill does in abstract terms without providing any concrete configuration details, wasting tokens on meta-description rather than actionable content. | 1 / 3 |
Actionability | No concrete code, commands, or configuration examples are provided. The skill claims to provide 'step-by-step guidance' and 'production-ready code' but contains none - only vague descriptions of what it could do. | 1 / 3 |
Workflow Clarity | No workflow is defined. For Triton Inference Server configuration, there should be clear steps for creating config.pbtxt files, model repository structure, and validation - none of which are present. | 1 / 3 |
Progressive Disclosure | The content is a flat, uninformative structure with no references to detailed materials, no examples, and no links to Triton documentation or related configuration files. | 1 / 3 |
Total | 4 / 12 Passed |
Validation
81%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 9 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
allowed_tools_field | 'allowed-tools' contains unusual tool name(s) | Warning |
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
Total | 9 / 11 Passed | |
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