Layer 2: Design Choices
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AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionm14-mental-modelExecute the skills CLI command in your project's root directory to begin installation:
Fetches m14-mental-model from actionbook/rust-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate m14-mental-model. Access via /m14-mental-model in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
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Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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Layer 2: Design Choices
What's the right way to think about this Rust concept?
When learning or explaining Rust:
| Concept | Mental Model | Analogy |
|---|---|---|
| Ownership | Unique key | Only one person has the house key |
| Move | Key handover | Giving away your key |
&T |
Lending for reading | Lending a book |
&mut T |
Exclusive editing | Only you can edit the doc |
Lifetime 'a |
Valid scope | "Ticket valid until..." |
Box<T> |
Heap pointer | Remote control to TV |
Rc<T> |
Shared ownership | Multiple remotes, last turns off |
Arc<T> |
Thread-safe Rc | Remotes from any room |
| From | Key Shift |
|---|---|
| Java/C# | Values are owned, not references by default |
| C/C++ | Compiler enforces safety rules |
| Python/Go | No GC, deterministic destruction |
| Functional | Mutability is safe via ownership |
| JavaScript | No null, use Option instead |
When confused about Rust:
What's the ownership model?
What guarantee is Rust providing?
What's the compiler telling me?
To design understanding (Layer 2):
"Why can't I do X in Rust?"
↑ Ask: What safety guarantee would be violated?
↑ Check: m01-m07 for the rule being enforced
↑ Ask: What's the intended design pattern?
To implementation (Layer 1):
"I understand the concept, now how do I implement?"
↓ m01-ownership: Ownership patterns
↓ m02-resource: Smart pointer choice
↓ m07-concurrency: Thread safety
| Error | Wrong Model | Correct Model |
|---|---|---|
| E0382 use after move | GC cleans up | Ownership = unique key transfer |
| E0502 borrow conflict | Multiple writers OK | Only one writer at a time |
| E0499 multiple mut borrows | Aliased mutation | Exclusive access for mutation |
| E0106 missing lifetime | Ignoring scope | References have validity scope |
E0507 cannot move from &T |
Implicit clone | References don't own data |
| Deprecated | Better |
|---|---|
| "Rust is like C++" | Different ownership model |
| "Lifetimes are GC" | Compile-time validity scope |
| "Clone solves everything" | Restructure ownership |
| "Fight the borrow checker" | Work with the compiler |
"unsafe to avoid rules" |
Understand safe patterns first |
Stack Heap
+----------------+ +----------------+
| main() | | |
| s1 ─────────────────────> │ "hello" |
| | | |
| fn takes(s) { | | |
| s2 (moved) ─────────────> │ "hello" |
| } | | (s1 invalid) |
+----------------+ +----------------+
After move: s1 is no longer valid
+----------------+
| data: String |────────────> "hello"
+----------------+
↑
│ &data (immutable borrow)
│
+------+------+
| reader1 reader2 (multiple OK)
+------+------+
+----------------+
| data: String |────────────> "hello"
+----------------+
↑
│ &mut data (mutable borrow)
│
+------+
| writer (only one)
+------+
| Stage | Focus | Skills |
|---|---|---|
| Beginner | Ownership basics | m01-ownership, m14-mental-model |
| Intermediate | Smart pointers, error handling | m02, m06 |
| Advanced | Concurrency, unsafe | m07, unsafe-checker |
| Expert | Design patterns | m09-m15, domain-* |
| When | See |
|---|---|
| Ownership errors | m01-ownership |
| Smart pointers | m02-resource |
| Concurrency | m07-concurrency |
| Anti-patterns | m15-anti-pattern |
Make data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
I recommend m14-mental-model for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
m14-mental-model fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Useful defaults in m14-mental-model — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Solid pick for teams standardizing on skills: m14-mental-model is focused, and the summary matches what you get after install.
m14-mental-model has been reliable in day-to-day use. Documentation quality is above average for community skills.
Solid pick for teams standardizing on skills: m14-mental-model is focused, and the summary matches what you get after install.
m14-mental-model has been reliable in day-to-day use. Documentation quality is above average for community skills.
We added m14-mental-model from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Keeps context tight: m14-mental-model is the kind of skill you can hand to a new teammate without a long onboarding doc.
I recommend m14-mental-model for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
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