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ruview-applications

Run RuView sensing applications — presence/occupancy, breathing & heart rate, activity & fall detection, 17-keypoint pose estimation (WiFlow), sleep monitoring & apnea screening, environment mapping, Mass Casualty Assessment (MAT), and the 3D point-cloud fusion demo. Use when someone wants to actually *do* something with a working RuView setup.

74

Quality

92%

Does it follow best practices?

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SecuritybySnyk

Passed

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SKILL.md
Quality
Evals
Security

Quality

Content

100%

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

An efficient, actionable router skill: compact tables and executable commands, a clear modality-selection decision flow, and well-structured one-level-deep references. Little to improve beyond adding validation hints for the live-sensing commands.

DimensionReasoningScore

Conciseness

Lean and token-efficient — a dense catalogue table plus terse commented recipe blocks, assuming Claude's competence without explaining CSI, Docker, or cargo; every line earns its place.

3 / 3

Actionability

Provides concrete, copy-paste-ready commands throughout (docker run, cargo run -p, node scripts/..., python examples/...) with per-application entry points, matching the executable-code anchor.

3 / 3

Workflow Clarity

A clear decision flow ('Picking the right modality' situation→modality) followed by ordered runnable recipes; no destructive/batch operations require checkpoints, and the simple-skills note permits 3 for unambiguous action.

3 / 3

Progressive Disclosure

Well-organized into clearly labeled sections (catalogue, recipes, modality picker, examples map, reference) with one-level-deep pointers to examples READMEs, docs, ADRs, and sibling skills; no monolithic wall of text.

3 / 3

Total

12

/

12

Passed

Description

85%

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

A strong description: comprehensive in naming concrete capabilities and clear in its use-trigger, with a distinctive niche. The main weakness is the trigger clause being somewhat generic and the reliance on domain jargon over natural layperson terms.

Suggestions

Rewrite the trigger clause to use natural user phrasing, e.g. 'Use when the user wants to detect people through walls, monitor breathing/heart rate, track falls, or run a RuView sensing app.'

Add a few common-synonym trigger terms users would actually say (e.g. 'occupancy sensing', 'sleep tracking', 'motion detection') alongside the domain jargon.

DimensionReasoningScore

Specificity

Lists many specific concrete actions — presence/occupancy, breathing & heart rate, fall detection, 17-keypoint pose estimation, apnea screening, MAT, 3D point-cloud fusion — matching the anchor that enumerates multiple specific actions.

3 / 3

Completeness

Explicitly answers both what (the sensing-application catalogue) and when via an explicit 'Use when...' trigger clause, matching the score-3 anchor pattern.

3 / 3

Trigger Term Quality

Includes some natural terms (breathing, heart rate, fall detection) but the dominant trigger clause is abstract ('Use when someone wants to actually do something with a working RuView setup') and the rest leans on domain-internal jargon (WiFlow, MAT), missing common user variations.

2 / 3

Distinctiveness Conflict Risk

Occupies a clear, distinctive niche (RuView sensing applications tied to specific hardware) and is unlikely to trigger for unrelated skills.

3 / 3

Total

11

/

12

Passed

Validation

93%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

referenced_paths_exist

Referenced path issues: 8 missing

Warning

Total

15

/

16

Passed

Repository
ruvnet/RuView
Reviewed

Table of Contents

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