agentleFS
YougLin-devYougLin-dev/Aha-Loop/.agents/skills/research/SKILL.md

research

Skill181 starsChanged 9 months agoMITView on GitHub

Conducts deep technical research for Aha Loop stories. Use before implementing stories involving unfamiliar libraries or architectural decisions. Triggers on: research this, investigate, explore options, compare alternatives.

189 other projects use a version of this.

Adopted by

Most recently taken up by

Used with

Projects with it also use daily-arxiv, exp-eval and 10 more.

Other files people use alongside this one.

Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
  • LambenthanSkill

    daily-arxiv

    每日从 arXiv 拉取新论文,过滤相关性,auto-ingest 高优先级论文,检测 SOTA 更新

    Also in 5 projects that use this

  • LambenthanSkill

    exp-eval

    实验判决门:Review LLM 独立评判实验结果 → 4 种判决路径 → 自动更新 claims confidence、ideas status、graph edges

    Also in 5 projects that use this

  • truongtv22Skill

    Problem-Solving Techniques

    Apply systematic problem-solving techniques for complexity spirals (simplification cascades), innovation blocks (collision-zone thinking), recurring patterns (meta-pattern recognition), assumption constraints (inversion exercise), scale uncertainty (scale game), and dispatch when stuck. Techniques derived from Microsoft Amplifier project patterns adapted for immediate application.

    Also in 5 projects that use this

  • liufeng1976Skill

    setup-ts-deep-modules

    Wire dependency-cruiser into a TypeScript repo so each package is a deep module — implementation hidden in subfolders, reachable only through its entry-point files. User-invoked.

    Also in 43 projects that use this

  • skyllwtSkill

    exp-pilot-eval

    Pilot result evaluation — read pilot results, apply success criteria, update idea page (pilot_result, failure_reason if failed), generate PILOT_VERDICT_REPORT. Called by /ideate Phase 5 after /exp-pilot-run.

    Also in 4 projects that use this

  • skyllwtSkill

    exp-pilot-run

    Pilot experiment execution — read Pilot Spec YAML, write pilot code, run experiment(Confirm with the user before operation and require the applicant to conduct manual inspection), return results. Called by /ideate Phase 5. Does NOT modify wiki pages or judge pass/fail.

    Also in 4 projects that use this

  • +5 more from Lambenthan
  • +1 more from skyllwt

The file

Show its rules and text

We split this skill into the rules it gives an agent

18 rules. 0 are common, 12 are distinctive, and 6 are very specific to this project.

  • 0

    Common

    Most of the 169 edited versions we read keep these.

  • 12

    Distinctive

    This author's own choices. Worth a look.

  • 6

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

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

    line 12
  2. Distinctive:

    Search documentation and best practices

    line 25
  3. Distinctive:

    Update knowledge base with findings

    line 28
  4. Very specific:

    Read the current story from prd.json and extract:

    line 37
  5. Very specific:

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

    line 58
  6. Distinctive:

    When researching or recommending libraries, always check for and prefer the latest stable version unless there's a specific compatibility …

    line 66
  7. Distinctive:

    Check GitHub issues for critical bugs

    line 88
  8. Distinctive:

    Always document version decisions:

    line 98
  9. Distinctive:

    Only use older versions when:

    line 114
  10. Distinctive:

    Use semantic search to find relevant code sections

    line 148
  11. Very specific:

    Look for examples/ directory for usage patterns

    line 150
  12. Very specific:

    Check tests/ for edge cases and proper usage

    line 151
  13. Very specific:

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

    line 162
  14. Distinctive:

    When multiple solutions exist, create a comparison:

    line 166
  15. Distinctive:

    Add patterns specific to THIS project:

    line 257
  16. Distinctive:

    Add reusable technical knowledge:

    line 264
  17. Distinctive:

    When you read library source code, document your findings:

    line 284
  18. Distinctive:

    Before marking research complete:

    line 330

“Common” is measured: kept by at least 6 in 10 of the 169 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

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

  1. Identify research topics from the current story's researchTopics field
  2. Fetch third-party library source code if needed
  3. Search documentation and best practices
  4. Analyze and compare alternatives
  5. Generate a research report
  6. Update knowledge base with findings
  7. 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

  1. 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
  2. Verify stability:
    • Released at least 1-2 weeks ago (not bleeding edge)
    • Check GitHub issues for critical bugs
    • Review changelog for breaking changes
  3. 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):

  1. README.md - Understand design intent and quick-start examples
  2. Entry Point Files:
    • Rust: src/lib.rs, src/main.rs
    • TypeScript/JS: src/index.ts, index.js
    • Python: __init__.py, main.py
  3. Module Structure - Scan mod.rs files or directory structure
  4. Type Definitions - Find core structs, interfaces, types
  5. Target Functionality - Locate the specific feature you need
  6. 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:

CriterionOption AOption BOption 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:**
```[language]
// Example from source or docs

Topic 2: [Name]

...

Alternatives Comparison

CriterionOption AOption BRecommendation
............

Recommendation: [Option X] because [reasoning]

Implementation Recommendations

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

  1. [Specific implementation guidance]
  2. [Pattern to follow]
  3. [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

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.