Agent Skillsmadebyaris/chaca-scanner › sdd-research

sdd-research

GitHub

用于在技术路径不明确或规划前,通过标准或深度模式调查代码库模式及外部解决方案,辅助制定规范与计划。

.cursor/skills/sdd-research/SKILL.md madebyaris/chaca-scanner

Trigger Scenarios

技术方法不明确 探索现有解决方案 分析代码库模式 执行/plan或/specify命令前

Install

npx skills add madebyaris/chaca-scanner --skill sdd-research -g -y
More Options

Use without installing

npx skills use madebyaris/chaca-scanner@sdd-research

指定 Agent (Claude Code)

npx skills add madebyaris/chaca-scanner --skill sdd-research -a claude-code -g -y

安装 repo 全部 skill

npx skills add madebyaris/chaca-scanner --all -g -y

预览 repo 内 skill

npx skills add madebyaris/chaca-scanner --list

SKILL.md

Frontmatter
{
    "name": "sdd-research",
    "description": "Pattern investigation and technical research before specification. Use when technical approach is unclear, exploring existing solutions, or analyzing codebase patterns. Supports deep research mode for thorough external investigation."
}

SDD Research Skill

Investigate codebase patterns and external solutions to inform specification and planning. Supports two modes: standard (codebase-focused) and deep (comprehensive external investigation).

When to Use

  • Technical approach is unclear
  • Need to understand existing patterns
  • Evaluating solution options
  • Before /specify or /plan commands
  • Deep research: New domain, unfamiliar technology, high-stakes architectural decision, or when standard research yields insufficient clarity

Research Modes

Standard Research (default)

Quick internal + surface external analysis. Good for well-understood domains where the codebase already has relevant patterns.

Deep Research

Multi-pass external investigation using web search and documentation fetching. Use when:

  • Entering an unfamiliar technology domain
  • Comparing multiple complex solutions (e.g. auth providers, database engines, deployment platforms)
  • The decision has high cost-of-reversal (architecture, data model, vendor lock-in)
  • Standard research leaves too many unknowns

Trigger: User requests deep research explicitly, or the agent detects high uncertainty after Phase 1.

Research Protocol

Phase 1: Codebase Analysis

  1. Existing patterns — how similar problems are solved
  2. Reusable components — what can be leveraged
  3. Conventions — naming, structure, architecture patterns
  4. Dependencies — libraries/frameworks in use

Run scripts/scan-patterns.sh to auto-detect project stack before manual exploration.

Phase 2: External Solutions (Standard)

  1. Best practices — industry standards for this problem
  2. Library options — available tools and tradeoffs
  3. Architecture patterns — applicable design patterns

Phase 2-Deep: Deep External Research (when deep mode is active)

Perform iterative, multi-pass investigation:

Pass 1 — Landscape scan:

  • Use WebSearch to survey the solution space (e.g. "best [technology] for [use case] 2026")
  • Identify the top 3-5 candidates from search results
  • Note official documentation URLs for each candidate

Pass 2 — Documentation deep-dive:

  • Use WebFetch to read official docs, getting-started guides, and API references for each candidate
  • Extract: API surface, pricing model, limits, supported platforms, migration path
  • Note version numbers and last-updated dates (reject stale/abandoned projects)

Pass 3 — Real-world validation:

  • Search for "[candidate] vs [candidate]" comparisons, benchmarks, and post-mortems
  • Search for "[candidate] production issues" or "[candidate] limitations"
  • Look for community size indicators: GitHub stars, npm weekly downloads, Stack Overflow activity

Pass 4 — Integration feasibility:

  • Check compatibility with the project's detected stack (from Phase 1)
  • Search for "[candidate] + [framework]" integration guides
  • Identify required changes to existing architecture

Deep research output additions:

  • Source URLs for all claims (linked in the research doc)
  • Confidence level per finding (High / Medium / Low — based on source quality)
  • "Last verified" date for each external fact

Phase 3: Synthesis

  1. Compare options — pros/cons matrix with weighted criteria
  2. Recommend approach — based on findings, with confidence level
  3. Flag risks — technical concerns and unknowns
  4. Deep research only: Include source bibliography and confidence assessment

Output Format

# Research: [Topic]

## Summary
[1-2 sentence overview]
**Research mode:** Standard | Deep
**Confidence:** High | Medium | Low

## Codebase Analysis
### Existing Patterns
| Pattern | Location | Relevance |

### Reusable Components
- [component]: [how to leverage]

## External Solutions
### Option 1: [Name]
- **Pros**: | **Cons**: | **Effort**:
- **Source**: [URL] (deep research only)

## Comparison Matrix
| Criteria | Weight | Option 1 | Option 2 |

## Recommendation
[Recommended approach with rationale]
**Confidence:** [High/Medium/Low] — [why]

## Risks & Unknowns
- [risk]: [mitigation]

## Sources (deep research only)
- [URL]: [what was learned]

References

  • references/patterns.md — Common architectural patterns
  • references/deep-research-guide.md — Deep research methodology, search strategies, and source evaluation criteria

Scripts

  • scripts/scan-patterns.sh [project-root] — Auto-detect frameworks, languages, testing tools, and project structure conventions

Integration

  • Findings feed into /specify and sdd-planner subagent
  • Can be invoked by sdd-explorer for deeper analysis
  • Use the ask question tool when research reveals multiple valid approaches
  • Deep research mode uses WebSearch and WebFetch tools extensively — ensure sandbox allows outbound access

Version History

  • 79928fe Current 2026-07-25 11:30

Same Skill Collection

.cursor/skills/anti-slop-design/SKILL.md
.cursor/skills/deep-research/SKILL.md
.cursor/skills/sdd-audit/SKILL.md
.cursor/skills/sdd-evolve/SKILL.md
.cursor/skills/sdd-implementation/SKILL.md
.cursor/skills/sdd-planning/SKILL.md

Metadata

Files
0
Version
79928fe
Hash
de02e190
Indexed
2026-07-25 11:30

Главная - Вики-сайт
Copyright © 2011-2026 iteam. Current version is 2.155.2. UTC+08:00, 2026-08-20 10:27
浙ICP备14020137号-1 $Гость$