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igmarin/rails-agent-skills

Curated library of 42 public AI agent skills for Ruby on Rails development, plus 5 callable workflow skills. Organized by category: planning, testing, code-quality, ddd, engines, infrastructure, api, patterns, context, orchestration, and workflows. Covers code review, architecture, security, testing (RSpec), engines, service objects, DDD patterns, and TDD automation.

75

Quality

94%

Does it follow best practices?

Impact

No eval scenarios have been run

SecuritybySnyk

Passed

No known issues

Overview
Quality
Evals
Security
Files

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 an excellent skill description that clearly defines a specific niche (Rails engine extraction), lists concrete actions, provides explicit 'Use when' guidance, and includes a comprehensive set of natural trigger terms. It uses proper third-person voice throughout and would be easily distinguishable from other skills in a large collection.

DimensionReasoningScore

Specificity

Lists multiple specific concrete actions: scaffolds engine structure, moves POROs/services/controllers incrementally, creates adapter interfaces to decouple host dependencies, and verifies regression coverage throughout each extraction slice.

3 / 3

Completeness

Clearly answers both 'what' (scaffolds engine structure, moves code incrementally, creates adapter interfaces, verifies regression coverage) and 'when' ('Use when extracting existing Rails app code into a reusable engine') with explicit trigger words listed.

3 / 3

Trigger Term Quality

Includes a comprehensive set of natural trigger terms that a Rails developer would use: 'extract to engine', 'move feature to engine', 'host coupling', 'adapters', 'extraction slices', 'preserve behavior', 'incremental extraction', 'bounded feature'. These are domain-specific and natural.

3 / 3

Distinctiveness Conflict Risk

Highly distinctive niche: Rails engine extraction is a very specific task unlikely to conflict with other skills. The trigger terms like 'extract to engine', 'host coupling', and 'extraction slices' are unique to this domain.

3 / 3

Total

12

/

12

Passed

Implementation

92%

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, well-structured skill that provides clear, actionable guidance for Rails engine extraction. The hard gate rule, sequenced extraction order, pitfalls table, and concrete examples make it immediately useful. The only weakness is that referenced bundle files are not provided, making it impossible to verify the progressive disclosure chain works end-to-end.

Suggestions

Ensure the referenced bundle files (assets/examples.md, references/adapter_examples.md, assets/checklist.json) actually exist and contain the promised content (full adapter example, per-slice checklist)

DimensionReasoningScore

Conciseness

The content is lean and efficient. It avoids explaining what Rails engines are, what POROs are, or other concepts Claude already knows. Every section earns its place — the hard gate, extraction order, pitfalls table, and examples all add unique value without padding.

3 / 3

Actionability

Provides executable bash commands for file moves, complete Ruby code examples for both the extracted PORO and the adapter pattern, and specific rspec commands for verification. The examples are copy-paste ready and cover the two most critical patterns (moving code and creating adapters).

3 / 3

Workflow Clarity

The 7-step extraction order is clearly sequenced with explicit validation ('Keep regression coverage green throughout each slice'). The hard gate provides a critical constraint. Each slice has defined completion criteria (one coherent responsibility, minimal new public API, passing regression tests, clear next step). The example includes a verification step before proceeding.

3 / 3

Progressive Disclosure

The skill references external files (assets/examples.md, references/adapter_examples.md, assets/checklist.json) which is good structure, but no bundle files were provided to verify these exist. The inline content is well-organized with compact examples and clear pointers, but the referenced files' absence means we can't confirm the progressive disclosure actually works.

2 / 3

Total

11

/

12

Passed

Validation

100%

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

Validation11 / 11 Passed

Validation for skill structure

No warnings or errors.

Reviewed

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