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learning-a-tool

Create learning paths for programming tools, and define what information should be researched to create learning guides. Use when user asks to learn, understand, or get started with any programming tool, library, or framework.

76

Quality

93%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

87%Weight 40%Scale 1-3

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

The body is well-organized and lean, with concrete research, structure, and output guidance plus good progressive disclosure to a single reference file. Its main weakness is the absence of explicit validation/verification checkpoints in the workflow.

Suggestions

Add an explicit verification checkpoint after Phase 1 (e.g., 'Confirm all three research sources are populated before structuring') and after Phase 3 (e.g., 'Verify all five levels and the four output files exist').

Turn the 'Do NOT merge, skip, or rename levels' constraint into a checklist item Claude can tick off before declaring the learning path complete.

Specify how Claude should locate repository metadata and community tutorials (e.g., GitHub API, search strategy) so the research phase is fully actionable rather than itemized.

DimensionReasoningScore

Conciseness

Lean bullet checklists for research, structure, and output with no basic-concept padding; every line carries actionable information and assumes Claude's competence.

3 / 3

Actionability

As an instruction-only skill it gives concrete guidance: named research items, an exact five-level ordering, and a specific output folder with named files, so absence of code is not penalized.

3 / 3

Workflow Clarity

The three phases (Research→Structure→Output) are sequenced, but there are no explicit validation or verification checkpoints confirming research completeness or output correctness before proceeding.

2 / 3

Progressive Disclosure

SKILL.md stays an overview and delegates level-detail content to a real, one-level-deep reference (references/progressive-learning.md) that is clearly signaled as the source of truth.

3 / 3

Total

11

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12

Passed

Description

100%Weight 40%Scale 1-3

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 well-crafted description that states concrete capabilities, includes natural trigger terms, and explicitly defines both what the skill does and when to invoke it. It is concise, specific, and uses correct third-person voice.

DimensionReasoningScore

Specificity

Names multiple concrete actions — 'Create learning paths for programming tools' and 'define what information should be researched to create learning guides' — rather than vague language.

3 / 3

Completeness

Explicitly answers both 'what' (create learning paths and define research scope) and 'when' via a 'Use when user asks to learn…' clause.

3 / 3

Trigger Term Quality

Covers natural terms users would say — 'learn, understand, or get started' plus 'programming tool, library, or framework' — giving good keyword coverage.

3 / 3

Distinctiveness Conflict Risk

Occupies a clear niche (learning guides for programming tools) with distinct triggers and third-person voice, making misfiring unlikely.

3 / 3

Total

12

/

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.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
https-deeplearning-ai/sc-agent-skills-files
Reviewed

Table of Contents

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