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learning-opportunities

Facilitates deliberate skill development during AI-assisted coding. Offers interactive learning exercises after architectural work (new files, schema changes, refactors). Use when completing features, making design decisions, or when user asks to understand code better. Triggers on "learning exercise", "help me understand", "teach me", "why does this work", or after creating new files/modules. Do NOT use for urgent debugging, quick fixes, or when user says "just ship it".

74

Quality

91%

Does it follow best practices?

Impact

No eval scenarios have been run

SecuritybySnyk

Passed

No known issues

SKILL.md
Quality
Evals
Security

Quality

Content

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 well-crafted skill that provides clear, actionable guidance for facilitating learning exercises during coding sessions. Its greatest strengths are the concrete dialogue examples with explicit stop points and the efficient organization that avoids unnecessary explanation. The only notable weakness is the reference to a `references/PRINCIPLES.md` file that isn't provided in the bundle, and the content could benefit from slightly better progressive disclosure by separating detailed examples from the overview.

DimensionReasoningScore

Conciseness

The content is lean and efficient throughout. It avoids explaining concepts Claude already knows (like what middleware is or how auth works), and every section serves a clear purpose. The examples are illustrative without being padded, and the anti-patterns section is a concise bullet list rather than verbose explanations.

3 / 3

Actionability

The skill provides highly concrete, actionable guidance with specific dialogue examples showing exact phrasing, clear behavioral rules (stop after question mark), and graduated examples for each exercise type. The hands-on code exploration section even shows progression levels with specific example prompts.

3 / 3

Workflow Clarity

The workflow is clearly sequenced: when to offer → how to ask → core principle (pause for input) → exercise types with step-by-step interaction flows → follow-up patterns. Each exercise type includes explicit [STOP — wait for response] checkpoints, creating clear feedback loops. The when/when-not gates provide validation before even starting.

3 / 3

Progressive Disclosure

The skill references `references/PRINCIPLES.md` for underlying learning science, which is good progressive disclosure. However, no bundle files are provided, so this reference is unverifiable. The content itself is well-structured with clear sections, but the inline examples are somewhat lengthy and could potentially be split into a separate examples reference file for a cleaner overview.

2 / 3

Total

11

/

12

Passed

Description

89%

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 well-structured skill description with strong trigger term coverage, explicit 'Use when' and 'Do NOT use' clauses, and a distinctive niche. Its main weakness is that the specific capabilities could be more concrete — it says it 'offers interactive learning exercises' but doesn't detail what form those take (quizzes, code challenges, explanations, etc.).

Suggestions

Add more concrete action verbs describing what the skill produces, e.g., 'Generates code comprehension quizzes, explains architectural patterns, and creates hands-on refactoring challenges' instead of the vaguer 'offers interactive learning exercises'.

DimensionReasoningScore

Specificity

The description names the domain (skill development during AI-assisted coding) and some actions (offers interactive learning exercises after architectural work), but the concrete actions are somewhat vague — 'facilitates deliberate skill development' and 'offers interactive learning exercises' don't specify what those exercises look like or what concrete outputs are produced.

2 / 3

Completeness

Clearly answers both 'what' (facilitates skill development, offers interactive learning exercises after architectural work) and 'when' (explicit 'Use when' clause with triggers, plus 'Do NOT use' exclusions). The explicit trigger guidance and anti-patterns make this highly complete.

3 / 3

Trigger Term Quality

Excellent coverage of natural trigger terms: 'learning exercise', 'help me understand', 'teach me', 'why does this work', plus contextual triggers like 'after creating new files/modules'. These are phrases users would naturally say, and the negative triggers ('just ship it', urgent debugging) further refine matching.

3 / 3

Distinctiveness Conflict Risk

This skill occupies a clear niche — learning/teaching during coding — that is distinct from typical coding, debugging, or documentation skills. The explicit exclusions ('NOT for urgent debugging, quick fixes') and specific trigger phrases like 'teach me' and 'learning exercise' make it unlikely to conflict with other skills.

3 / 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.

Repository
tech-leads-club/agent-skills
Reviewed

Table of Contents

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