m14-mental-model
Use when learning Rust concepts. Keywords: mental model, how to think about ownership, understanding borrow checker, visualizing memory layout, analogy, misconception, explaining ownership, why does Rust, help me understand, confused about, learning Rust, explain like I'm, ELI5, intuition for, coming from Java, coming from Python, 心智模型, 如何理解所有权, 学习 Rust, Rust 入门, 为什么 Rust
Install with Tessl CLI
npx tessl i github:actionbook/rust-skills --skill m14-mental-model70
Does it follow best practices?
If you maintain this skill, you can automatically optimize it using the tessl CLI to improve its score:
npx tessl skill review --optimize ./path/to/skillValidation for skill structure
Discovery
37%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 description has excellent trigger term coverage with natural phrases users would say when learning Rust, including multilingual support. However, it critically fails to describe what the skill actually does - it's essentially just a keyword list with no capability description. The complete absence of action verbs or concrete capabilities makes it impossible to know what help this skill provides.
Suggestions
Add a capability statement at the beginning describing what the skill does, e.g., 'Explains Rust concepts through analogies, mental models, and visualizations. Helps developers understand ownership, borrowing, and lifetimes by relating them to familiar concepts from other languages.'
Structure the description with 'what' first, then 'when/keywords', e.g., 'Teaches Rust fundamentals through intuitive explanations and analogies for developers from other language backgrounds. Use when...'
Remove redundant keywords and consolidate into a cleaner format - the current list is comprehensive but the lack of any action description undermines its usefulness for skill selection.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | The description lacks any concrete actions. It only says 'Use when learning Rust concepts' without specifying what the skill actually does - no verbs describing capabilities like 'explains', 'visualizes', 'teaches', or 'provides analogies'. | 1 / 3 |
Completeness | The description answers 'when' extensively with keywords but completely fails to answer 'what does this do'. There is no explanation of the skill's capabilities or actions - only trigger conditions and keywords. | 1 / 3 |
Trigger Term Quality | Excellent coverage of natural trigger terms users would say: 'help me understand', 'confused about', 'explain like I'm', 'ELI5', 'coming from Java/Python', plus specific Rust concepts like 'ownership', 'borrow checker', and even Chinese equivalents for international users. | 3 / 3 |
Distinctiveness Conflict Risk | The Rust-specific keywords and concepts like 'ownership', 'borrow checker', and 'memory layout' create some distinctiveness, but without stating what the skill does, it could overlap with any Rust-related skill (documentation, coding, debugging). | 2 / 3 |
Total | 7 / 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-crafted conceptual skill that efficiently delivers mental models for Rust learning through tables, analogies, and visualizations. Its strength is in concise organization and clear cross-referencing to implementation skills. The main weakness is limited actionability - while appropriate for a 'mental model' skill, adding 1-2 concrete code examples showing how to apply these models when debugging would strengthen it.
Suggestions
Add a brief concrete example showing how to apply the 'Thinking Prompt' questions to a real borrow checker error and its resolution
Include one executable code snippet in the 'Common Misconceptions' section demonstrating the correct pattern for a frequent error like E0382
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Extremely lean and efficient use of tables and visualizations. No unnecessary explanations of basic concepts - assumes Claude understands programming and can apply analogies directly. | 3 / 3 |
Actionability | Provides mental models and analogies rather than executable code, which is appropriate for a conceptual skill. However, the 'Thinking Prompt' section gives concrete questions to ask but lacks specific examples of applying these models to real code scenarios. | 2 / 3 |
Workflow Clarity | For a conceptual/educational skill, the workflow is clear: identify confusion → check mental model → trace to related skills. The 'Trace Up/Down' sections provide explicit navigation paths, and the Learning Path table sequences progression appropriately. | 3 / 3 |
Progressive Disclosure | Excellent structure with clear sections, well-organized tables, and explicit one-level-deep references to related skills (m01-m15). The 'Related Skills' section provides clear navigation without nested indirection. | 3 / 3 |
Total | 11 / 12 Passed |
Validation
68%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 11 / 16 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
description_voice | 'description' should use third person voice; found first person: 'I'm' | Warning |
metadata_version | 'metadata' field is not a dictionary | Warning |
license_field | 'license' field is missing | Warning |
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
body_output_format | No obvious output/return/format terms detected; consider specifying expected outputs | Warning |
Total | 11 / 16 Passed | |
- Reviewed
Table of Contents
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