research

Conduct thorough technical research before implementation to ensure high-quality, informed decisions.

Safety Notice

This listing is imported from skills.sh public index metadata. Review upstream SKILL.md and repository scripts before running.

Copy this and send it to your AI assistant to learn

Install skill "research" with this command: npx skills add youglin-dev/aha-loop/youglin-dev-aha-loop-research

Deep Research Skill

Conduct thorough technical research before implementation to ensure high-quality, informed decisions.

Workspace Mode Note

When running in workspace mode, all paths are relative to .aha-loop/ directory:

  • Research reports: .aha-loop/research/ (not scripts/aha-loop/research/ )

  • Knowledge base: .aha-loop/knowledge/ (not knowledge/ )

  • Vendor directory: .aha-loop/.vendor/ (not .vendor/ )

The orchestrator will provide the actual paths in the prompt context.

The Job

  • Identify research topics from the current story's researchTopics field

  • Fetch third-party library source code if needed

  • Search documentation and best practices

  • Analyze and compare alternatives

  • Generate a research report

  • Update knowledge base with findings

  • Mark researchCompleted: true in prd.json

Research Process

Step 1: Identify What to Research

Read the current story from prd.json and extract:

  • researchTopics

  • explicit topics to investigate

  • Dependencies mentioned in acceptance criteria

  • Patterns referenced in the description

Also check:

  • Previous story's learnings field for follow-up research needs

  • knowledge/project/gotchas.md for related known issues

Step 2: Fetch Library Source Code (If Needed)

For any third-party library research, fetch the source:

Fetch specific library

./scripts/aha-loop/fetch-source.sh rust tokio 1.35.0

Or fetch all project dependencies

./scripts/aha-loop/fetch-source.sh --from-deps

After fetching, the source will be at .vendor/<ecosystem>/<name>-<version>/

Library Version Selection

Always Prefer Latest Stable Versions

When researching or recommending libraries, always check for and prefer the latest stable version unless there's a specific compatibility reason not to.

Version Research Process

Query the package registry for latest version:

Rust (crates.io)

curl -s "https://crates.io/api/v1/crates/tokio" | jq '.crate.max_stable_version'

Or use cargo

cargo search tokio --limit 1

Node.js (npm)

npm view react version

Python (PyPI)

pip index versions requests 2>/dev/null | head -1

Verify stability:

  • Released at least 1-2 weeks ago (not bleeding edge)

  • Check GitHub issues for critical bugs

  • Review changelog for breaking changes

Check compatibility:

  • Works with existing project dependencies

  • Compatible with project's minimum supported language version

  • No known conflicts

Version Documentation

Always document version decisions:

Version Decision: [Library Name]

Selected Version: X.Y.Z Latest Available: X.Y.Z (as of YYYY-MM-DD) Reason: [Why this version was chosen]

Compatibility Notes:

  • Works with [other dependency] v[X.Y]
  • Requires [language] v[X.Y]+

When to Use Older Versions

Only use older versions when:

  • Latest version has critical bugs

  • Incompatible with required dependencies

  • Breaking changes require significant refactoring

  • Project explicitly constrains the version

Always document the reason in knowledge/project/decisions.md :

ADR: Using [Library] v[Old] instead of v[New]

Context: [Why we're not using latest] Decision: Pin to v[Old] Consequences: [What we're missing, when to revisit]

Step 3: Read Source Code Strategically

Reading Order (Most Important First):

  • README.md - Understand design intent and quick-start examples

  • Entry Point Files:

  • Rust: src/lib.rs , src/main.rs

  • TypeScript/JS: src/index.ts , index.js

  • Python: init.py , main.py

  • Module Structure - Scan mod.rs files or directory structure

  • Type Definitions - Find core structs, interfaces, types

  • Target Functionality - Locate the specific feature you need

  • Tests - Learn correct usage patterns from test files

Reading Tips:

  • Use semantic search to find relevant code sections

  • Focus on PUBLIC APIs, skip internal implementation unless needed

  • Look for examples/ directory for usage patterns

  • Check tests/ for edge cases and proper usage

Step 4: Web Search for Context

Search for:

  • Official documentation

  • Best practices and common patterns

  • Known issues and gotchas

  • Performance considerations

  • Alternative libraries

Use MCP tools like context7 for up-to-date documentation.

Step 5: Compare Alternatives (If Applicable)

When multiple solutions exist, create a comparison:

Criterion Option A Option B Option C

Performance ... ... ...

API Ergonomics ... ... ...

Maintenance Status ... ... ...

Bundle Size ... ... ...

Learning Curve ... ... ...

Include a recommendation with reasoning.

Research Report Template

Save to: scripts/aha-loop/research/[story-id]-research.md

Research Report: [Story ID] - [Story Title]

Date: YYYY-MM-DD Status: Complete | Needs Follow-up

Research Topics

  1. [Topic from researchTopics array]
  2. ...

Findings

Topic 1: [Name]

Summary: Brief answer to the research question

Source Code Analysis:

  • Library: [name] v[version]
  • Key File: .vendor/rust/tokio-1.35.0/src/runtime/mod.rs
  • Relevant Code: Lines 123-189
  • Pattern Observed: [description]

Documentation Notes:

  • [Key insight from docs]
  • [Another insight]

Code Example:

// Example from source or docs

Topic 2: [Name]

...

Alternatives Comparison

Criterion
Option A
Option B
Recommendation

...
...
...
...

Recommendation: [Option X] because [reasoning]

Implementation Recommendations

Based on research, the story should be implemented as follows:

- [Specific implementation guidance]

- [Pattern to follow]

- [Pitfalls to avoid]

Follow-up Research Needed

-  [Topic that needs deeper investigation]

-  [Question that emerged during research]

Knowledge Base Updates

The following should be added to knowledge base:

To knowledge/project/patterns.md
:

- [Pattern specific to this project]

To knowledge/domain/[topic]/
:

- [Reusable knowledge about a library or technique]

---

## Updating Knowledge Base

### Project Knowledge (`knowledge/project/`)

Add patterns specific to THIS project:
- How this codebase uses a library
- Project-specific conventions discovered
- Gotchas specific to this codebase

### Domain Knowledge (`knowledge/domain/`)

Add reusable technical knowledge:
- Library usage patterns (applicable to any project)
- Comparison documents
- Best practices

**Create new topic directories as needed:**

knowledge/domain/
└── [topic-name]/
├── README.md           # Overview
├── patterns.md         # Common patterns
├── gotchas.md          # Known issues
└── examples/           # Code examples

---

## Source Code Reading Report

When you read library source code, document your findings:

```markdown
## Source Code Analysis: [Library] v[Version]

### Module Structure

src/
├── lib.rs          # Main entry, exports public API
├── runtime/        # Async runtime implementation
│   ├── mod.rs      # Module exports
│   └── scheduler.rs # Task scheduling
└── sync/           # Synchronization primitives

### Key Types

- `Runtime` (src/runtime/mod.rs:45) - Main runtime struct
- `Handle` (src/runtime/handle.rs:23) - Runtime handle for spawning

### Key Functions

- `Runtime::new()` (L89-L120) - Creates new runtime with default config
- `spawn()` (L156-L189) - Spawns a new async task

### Usage Patterns from Tests

From `tests/runtime.rs:34`:
```rust
let rt = Runtime::new().unwrap();
rt.block_on(async {
    // ...
});

Important Notes

- Thread safety: Runtime is Send + Sync

- Performance: Use spawn_blocking
 for CPU-heavy tasks

- Gotcha: Don't call block_on
 from async context

---

## Checklist

Before marking research complete:

- [ ] All `researchTopics` investigated
- [ ] Library source code fetched and key files read (if applicable)
- [ ] Web search performed for documentation and best practices
- [ ] Alternatives compared (if multiple options exist)
- [ ] Research report saved to `scripts/aha-loop/research/`
- [ ] Knowledge base updated with reusable findings
- [ ] Implementation recommendations documented
- [ ] `researchCompleted: true` set in prd.json

Source Transparency

This detail page is rendered from real SKILL.md content. Trust labels are metadata-based hints, not a safety guarantee.

Related Skills

Related by shared tags or category signals.

Coding

roadmap

No summary provided by upstream source.

Repository SourceNeeds Review
Coding

god-intervention

No summary provided by upstream source.

Repository SourceNeeds Review
Coding

god-member

No summary provided by upstream source.

Repository SourceNeeds Review