inference-latency-profiler
Inference Latency Profiler - Auto-activating skill for ML Deployment. Triggers on: inference latency profiler, inference latency profiler Part of the ML Deployment skill category.
Install with Tessl CLI
npx tessl i github:jeremylongshore/claude-code-plugins-plus-skills --skill inference-latency-profilerOverall
score
19%
Does it follow best practices?
Validation for skill structure
Activation
7%This description is essentially a placeholder that provides almost no useful information for skill selection. It only states the skill name and category without describing capabilities, actions, or meaningful trigger conditions. The duplicate trigger term suggests this was auto-generated without human refinement.
Suggestions
Add specific actions the skill performs, e.g., 'Measures model inference time, identifies bottlenecks in prediction pipelines, generates latency reports, and suggests optimization strategies.'
Include a 'Use when...' clause with natural trigger terms like 'slow predictions', 'model latency', 'inference speed', 'deployment performance', 'prediction time optimization'.
Remove the duplicate trigger term and expand with variations users might actually say when needing this skill.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | The description only names the skill ('Inference Latency Profiler') without describing any concrete actions. There are no verbs indicating what the skill actually does - no mention of measuring, analyzing, optimizing, or any specific capabilities. | 1 / 3 |
Completeness | The description fails to answer 'what does this do' beyond the name, and provides no 'when should Claude use it' guidance. The 'Triggers on' section just repeats the skill name rather than providing meaningful trigger scenarios. | 1 / 3 |
Trigger Term Quality | The trigger terms listed are just the skill name repeated twice ('inference latency profiler, inference latency profiler'). Missing natural user terms like 'slow inference', 'model speed', 'prediction time', 'latency issues', 'performance profiling', etc. | 1 / 3 |
Distinctiveness Conflict Risk | The term 'Inference Latency Profiler' is fairly specific to ML deployment contexts, which provides some distinctiveness. However, without concrete actions described, it could overlap with general ML performance or monitoring skills. | 2 / 3 |
Total | 5 / 12 Passed |
Implementation
0%This skill is essentially a placeholder with no substantive content. It describes what an inference latency profiler skill would do without providing any actual guidance, code, tools, or methodology. The entire content could be replaced with 'Help with inference latency profiling' and convey the same information.
Suggestions
Add concrete code examples showing how to profile inference latency (e.g., using Python's time module, PyTorch profiler, or TensorFlow profiler)
Include specific metrics to measure (P50/P95/P99 latency, throughput, batch size impact) and how to collect them
Provide a clear workflow: 1) Instrument model, 2) Run profiling, 3) Analyze bottlenecks, 4) Optimize, with validation steps
Add tool-specific guidance for common serving frameworks (TensorRT, ONNX Runtime, TorchServe) with executable examples
| 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 zero actionable information. | 1 / 3 |
Actionability | No concrete code, commands, or specific guidance is provided. The skill describes what it does in abstract terms but never shows how to actually profile inference latency - no tools, no metrics, no implementation details. | 1 / 3 |
Workflow Clarity | No workflow is defined. Claims to provide 'step-by-step guidance' but contains zero actual steps. There's no sequence, no validation checkpoints, and no process to follow. | 1 / 3 |
Progressive Disclosure | The content is a monolithic block of vague descriptions with no structure for discovery. No references to detailed documentation, no links to examples or advanced topics, and no meaningful organization of content. | 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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