m11-ecosystem

actionbook/rust-skills · updated Apr 8, 2026

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$npx skills add https://github.com/actionbook/rust-skills --skill m11-ecosystem
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summary

!grep -A 100 '^\[dependencies\]' Cargo.toml 2>/dev/null | head -30 || echo "No Cargo.toml found"

skill.md

Current Dependencies (Auto-Injected)

!grep -A 100 '^\[dependencies\]' Cargo.toml 2>/dev/null | head -30 || echo "No Cargo.toml found"


Ecosystem Integration

Layer 2: Design Choices

Core Question

What's the right crate for this job, and how should it integrate?

Before adding dependencies:

  • Is there a standard solution?
  • What's the maintenance status?
  • What's the API stability?

Integration Decision → Implementation

Need Choice Crates
Serialization Derive-based serde, serde_json
Async runtime tokio or async-std tokio (most popular)
HTTP client Ergonomic reqwest
HTTP server Modern axum, actix-web
Database SQL or ORM sqlx, diesel
CLI parsing Derive-based clap
Error handling App vs lib anyhow, thiserror
Logging Facade tracing, log

Thinking Prompt

Before adding a dependency:

  1. Is it well-maintained?

    • Recent commits?
    • Active issue response?
    • Breaking changes frequency?
  2. What's the scope?

    • Do you need the full crate or just a feature?
    • Can feature flags reduce bloat?
  3. How does it integrate?

    • Trait-based or concrete types?
    • Sync or async?
    • What bounds does it require?

Trace Up ↑

To domain constraints (Layer 3):

"Which HTTP framework should I use?"
    ↑ Ask: What are the performance requirements?
    ↑ Check: domain-web (latency, throughput needs)
    ↑ Check: Team expertise (familiarity with framework)
Question Trace To Ask
Framework choice domain-* What constraints matter?
Library vs build domain-* What's the deployment model?
API design domain-* Who are the consumers?

Trace Down ↓

To implementation (Layer 1):

"Integrate external crate"
    ↓ m04-zero-cost: Trait bounds and generics
    ↓ m06-error-handling: Error type compatibility

"FFI integration"
    ↓ unsafe-checker: Safety requirements
    ↓ m12-lifecycle: Resource cleanup

Quick Reference

Language Interop

Integration Crate/Tool Use Case
C/C++ → Rust bindgen Auto-generate bindings
Rust → C cbindgen Export C headers
Python ↔ Rust pyo3 Python extensions
Node.js ↔ Rust napi-rs Node addons
WebAssembly wasm-bindgen Browser/WASI

Cargo Features

Feature Purpose
[features] Optional functionality
default = [...] Default features
feature = "serde" Conditional deps
[workspace] Multi-crate projects

Error Code Reference

Error Cause Fix
E0433 Can't find crate Add to Cargo.toml
E0603 Private item Check crate docs
Feature not enabled Optional feature Enable in features
Version conflict Incompatible deps cargo update or pin
Duplicate types Different crate versions Unify in workspace

Crate Selection Criteria

Criterion Good Sign Warning Sign
Maintenance Recent commits Years inactive
Community Active issues/PRs No response
Documentation Examples, API docs Minimal docs
Stability Semantic versioning Frequent breaking
Dependencies Minimal, well-known Heavy, obscure

Anti-Patterns

Anti-Pattern Why Bad Better
extern crate Outdated (2018+) Just use
#[macro_use] Global pollution Explicit import
Wildcard deps * Unpredictable Specific versions
Too many deps Supply chain risk Evaluate necessity
Vendoring everything Maintenance burden Trust crates.io

Related Skills

When See
Error type design m06-error-handling
Trait integration m04-zero-cost
FFI safety unsafe-checker
Resource management m12-lifecycle
how to use m11-ecosystem

How to use m11-ecosystem on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add m11-ecosystem
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/actionbook/rust-skills --skill m11-ecosystem

The skills CLI fetches m11-ecosystem from GitHub repository actionbook/rust-skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/m11-ecosystem

Reload or restart Cursor to activate m11-ecosystem. Access the skill through slash commands (e.g., /m11-ecosystem) or your agent's skill management interface.

Security & Verification Notice

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 development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases

User Story & Requirements Generation

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

Competitive Analysis

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

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

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

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ 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.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.738 reviews
  • Diya Desai· Dec 24, 2024

    Useful defaults in m11-ecosystem — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Liam Ramirez· Dec 24, 2024

    Keeps context tight: m11-ecosystem is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Zaid Diallo· Dec 20, 2024

    m11-ecosystem fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Ganesh Mohane· Dec 16, 2024

    We added m11-ecosystem from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Harper Chawla· Dec 4, 2024

    m11-ecosystem has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Yash Thakker· Nov 27, 2024

    m11-ecosystem fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Diya Sanchez· Nov 15, 2024

    We added m11-ecosystem from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Noah Farah· Nov 15, 2024

    m11-ecosystem is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Sakshi Patil· Nov 7, 2024

    Useful defaults in m11-ecosystem — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Chaitanya Patil· Oct 26, 2024

    Registry listing for m11-ecosystem matched our evaluation — installs cleanly and behaves as described in the markdown.

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