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arn-spark-arch-vision

This skill should be used when the user says "arch vision", "architecture vision", "arn arch vision", "define the architecture", "tech stack", "what technology should I use", "design the system", "system architecture", "how should I build this", "technology choices", "choose technologies", "pick a tech stack", or wants to explore technology options and define the high-level architecture for a greenfield project. Takes a product concept as input and produces an architecture-vision.md document capturing the technology stack, system design, protocols, packaging strategy, and known risks.

74

Quality

92%

Does it follow best practices?

Impact

No eval scenarios have been run

SecuritybySnyk

Advisory

Suggest reviewing before use

SKILL.md
Quality
Evals
Security

Quality

Discovery

100%

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 is a strong skill description that excels across all dimensions. It provides an extensive list of natural trigger phrases, clearly defines both the input (product concept) and output (architecture-vision.md), and specifies the concrete contents of the deliverable. The description is well-scoped to greenfield architecture decisions, making it highly distinctive.

DimensionReasoningScore

Specificity

Lists multiple specific concrete actions: takes a product concept as input, produces an architecture-vision.md document, captures technology stack, system design, protocols, packaging strategy, and known risks.

3 / 3

Completeness

Clearly answers both 'what' (produces an architecture-vision.md document capturing technology stack, system design, protocols, packaging strategy, and known risks) and 'when' (explicit list of trigger phrases plus the general condition of wanting to explore technology options for a greenfield project).

3 / 3

Trigger Term Quality

Excellent coverage of natural trigger terms including variations like 'arch vision', 'architecture vision', 'tech stack', 'what technology should I use', 'how should I build this', 'design the system', 'choose technologies', and 'pick a tech stack'. These are phrases users would naturally say.

3 / 3

Distinctiveness Conflict Risk

Clearly scoped to greenfield project architecture vision with a specific output artifact (architecture-vision.md). The combination of architecture definition, tech stack selection, and greenfield context creates a distinct niche unlikely to conflict with other skills.

3 / 3

Total

12

/

12

Passed

Implementation

85%

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

This is a well-structured conversational workflow skill with excellent actionability and workflow clarity. The step-by-step process is clearly sequenced with validation checkpoints, decision tables for situational routing, and comprehensive error handling. The main weakness is moderate verbosity — the agent invocation guide is duplicated, and some conversational templates could be more concise — but overall the content earns its place by providing domain-specific guidance Claude wouldn't otherwise have.

DimensionReasoningScore

Conciseness

The skill is fairly long (~250 lines) and includes some redundancy (e.g., the agent invocation table appears twice — once inline in Step 3 and once as a standalone section). Some conversational templates could be trimmed. However, most content is domain-specific workflow guidance that Claude wouldn't inherently know, so it's not egregiously verbose.

2 / 3

Actionability

The skill provides highly concrete, step-by-step guidance with specific file paths, exact agent invocation patterns, structured data blocks to include in agent calls, decision tables for situational responses, and clear output artifacts. The conversation prompts are copy-paste ready and the template reference is explicit.

3 / 3

Workflow Clarity

The workflow is clearly sequenced (Steps 0-5) with explicit validation checkpoints: user confirmation after requirement extraction (Step 1), readiness check with pillar alignment assessment before writing (Step 3), and a comprehensive error handling section covering cancellation, failures, and existing documents. The iterative conversation loop has clear entry/exit conditions and a decision table for routing.

3 / 3

Progressive Disclosure

The skill references external files appropriately — the architecture vision template, technology evaluation guide, and configuration step are all delegated to separate reference files with clear paths. The main SKILL.md serves as the workflow overview without inlining content that belongs elsewhere. References are one level deep and clearly signaled.

3 / 3

Total

11

/

12

Passed

Validation

90%

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

Validation10 / 11 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

10

/

11

Passed

Repository
AppsVortex/arness
Reviewed

Table of Contents

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