prediction-monitor
Prediction Monitor - Auto-activating skill for ML Deployment. Triggers on: prediction monitor, prediction monitor Part of the ML Deployment skill category.
Install with Tessl CLI
npx tessl i github:jeremylongshore/claude-code-plugins-plus-skills --skill prediction-monitorOverall
score
19%
Does it follow best practices?
Validation for skill structure
Activation
7%This description is severely underdeveloped, functioning more as a label than a useful skill description. It provides no information about what capabilities the skill offers, what actions it can perform, or specific scenarios when it should be activated. The duplicate trigger term suggests a template that wasn't properly filled out.
Suggestions
Add specific capabilities describing what the skill does, e.g., 'Tracks prediction accuracy, detects model drift, monitors inference latency, and alerts on anomalies in deployed ML models.'
Include a 'Use when...' clause with natural trigger terms like 'model drift', 'prediction accuracy', 'inference monitoring', 'model performance tracking', 'production model health'.
Fix the duplicate trigger term and expand to include variations users would naturally say when needing this functionality.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | The description only names the skill ('Prediction Monitor') and its category ('ML Deployment') without describing any concrete actions. There are no verbs indicating what the skill actually does. | 1 / 3 |
Completeness | The description fails to answer 'what does this do' (no capabilities listed) and 'when should Claude use it' (no explicit use-case guidance beyond the generic trigger phrase). Both components are essentially missing. | 1 / 3 |
Trigger Term Quality | The trigger terms are redundant ('prediction monitor, prediction monitor' - duplicated) and overly narrow. Missing natural variations users might say like 'model monitoring', 'inference tracking', 'prediction drift', 'model performance', etc. | 1 / 3 |
Distinctiveness Conflict Risk | While 'prediction monitor' is somewhat specific to ML monitoring, the lack of detail about what distinguishes this from other ML-related skills (model training, deployment, evaluation) creates potential overlap risk within the ML Deployment category. | 2 / 3 |
Total | 5 / 12 Passed |
Implementation
0%This skill is essentially a placeholder with no substantive content. It describes what a prediction monitoring skill should do without providing any actual guidance, code, or actionable information. The entire content could be replaced with a single sentence and lose nothing of value.
Suggestions
Add concrete code examples for setting up prediction monitoring (e.g., tracking prediction latency, drift detection, alerting thresholds)
Define a clear workflow for implementing prediction monitoring: what metrics to track, how to set up dashboards, when to alert
Include specific tool recommendations with executable configuration examples (e.g., Prometheus metrics, Grafana dashboards, or cloud-native monitoring)
Remove all generic boilerplate ('provides automated assistance', 'follows best practices') and replace with actual technical content
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is padded with generic boilerplate that provides no actual information. Phrases like 'provides automated assistance' and 'follows industry best practices' are meaningless filler that Claude already understands conceptually. | 1 / 3 |
Actionability | There is zero concrete guidance - no code, no commands, no specific steps, no examples of actual prediction monitoring implementation. The content only describes what the skill claims to do without showing how to do anything. | 1 / 3 |
Workflow Clarity | No workflow is defined. There are no steps, no sequence, no validation checkpoints. The skill mentions 'step-by-step guidance' but provides none. | 1 / 3 |
Progressive Disclosure | No structure beyond generic headings. No references to detailed documentation, no links to examples or advanced topics. The content is both shallow and poorly organized. | 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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