wake-word-detection
Expert skill for implementing wake word detection with openWakeWord. Covers audio monitoring, keyword spotting, privacy protection, and efficient always-listening systems for JARVIS voice assistant.
68
58%
Does it follow best practices?
Impact
Pending
No eval scenarios have been run
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./skills/wake-word-detection/SKILL.mdQuality
Discovery
40%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
The description identifies a clear technical niche (openWakeWord for JARVIS) which provides good distinctiveness, but suffers from missing explicit trigger guidance and somewhat abstract capability descriptions. The lack of a 'Use when...' clause is a significant gap that would make it harder for Claude to know when to select this skill from a large pool.
Suggestions
Add a 'Use when...' clause with explicit triggers like 'Use when implementing wake word detection, setting up voice activation, configuring hotword recognition, or building always-listening features for JARVIS'.
Replace abstract terms like 'covers audio monitoring' with concrete actions like 'Configure microphone input streams, set detection thresholds, handle wake word callbacks'.
Include common user phrasings and synonyms like 'hotword', 'voice activation', 'hey jarvis', 'speech trigger' to improve trigger term coverage.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Names the domain (wake word detection with openWakeWord) and lists some actions (audio monitoring, keyword spotting, privacy protection, always-listening systems), but these are more like feature areas than concrete specific actions like 'detect wake words', 'configure sensitivity thresholds', or 'train custom wake words'. | 2 / 3 |
Completeness | Describes what the skill covers but completely lacks a 'Use when...' clause or any explicit trigger guidance. There's no indication of when Claude should select this skill, which per the rubric should cap completeness at 2, and since the 'when' is entirely missing, this scores a 1. | 1 / 3 |
Trigger Term Quality | Includes relevant terms like 'wake word', 'openWakeWord', 'keyword spotting', 'voice assistant', and 'JARVIS', but misses common variations users might say like 'hotword', 'activation phrase', 'hey jarvis', 'voice activation', or 'speech detection'. | 2 / 3 |
Distinctiveness Conflict Risk | The combination of 'openWakeWord', 'wake word detection', and 'JARVIS voice assistant' creates a very specific niche that is unlikely to conflict with other skills. The technology stack and use case are clearly defined. | 3 / 3 |
Total | 8 / 12 Passed |
Implementation
77%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a strong, actionable skill with excellent executable code examples and clear TDD workflow. The main weaknesses are verbosity in early sections (explaining concepts Claude knows) and the monolithic structure that could benefit from progressive disclosure to separate reference files. The performance patterns and security standards sections are particularly well-done with good/bad comparisons.
Suggestions
Remove or significantly condense sections 1-3 (Overview, Core Principles, Core Responsibilities) - these explain concepts Claude already understands and add ~50 lines of low-value content
Split detailed patterns (sections 6-8) into separate reference files (e.g., PATTERNS.md, PERFORMANCE.md) and keep only the primary SecureWakeWordDetector implementation in the main skill
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is reasonably efficient but includes some unnecessary sections like the overview explaining what wake word detection is and verbose explanations of principles Claude already understands. The 'Core Principles' and 'Core Responsibilities' sections could be condensed significantly. | 2 / 3 |
Actionability | Excellent executable code examples throughout - complete Python implementations for the detector, tests, performance patterns, and security controls. All code is copy-paste ready with proper imports and realistic implementations. | 3 / 3 |
Workflow Clarity | Clear TDD workflow with explicit steps (write failing test → implement minimum → verify). The pre-implementation checklist provides explicit validation checkpoints across three phases. Verification commands are concrete (pytest commands with coverage). | 3 / 3 |
Progressive Disclosure | Content is well-organized with clear sections, but it's a monolithic document that could benefit from splitting detailed patterns into separate files. The 400+ lines of content would be better served with a concise overview linking to PATTERNS.md, TESTS.md, etc. | 2 / 3 |
Total | 10 / 12 Passed |
Validation
75%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 12 / 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 |
metadata_version | 'metadata' field is not a dictionary | Warning |
license_field | 'license' field is missing | Warning |
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
Total | 12 / 16 Passed | |
- Repository
- martinholovsky/claude-skills-generator
- Commit
1086ef2
- Reviewed
Table of Contents
Is this your skill?
If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.