sdd-research
Skill198 starsChanged 5 months agoMITView on GitHub
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.
1 other project uses a version of this.
Adopted by
Most recently taken up by
- mariano-aguero/spec-driven-development-skilltheir own version, first seen Nov 8, 2026
Other versions1 project uses a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 1
- mariano-aguero/spec-driven-development-skill★ 11same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository6 other files it gives its agents.
- .cursor/rules/sdd-system.mdcCursor rule
- sdd-auditSkill
- sdd-evolveSkill
- sdd-implementationSkill
- sdd-memorySkill
- sdd-planningSkill
The file
We split this skill into the rules it gives an agent
10 rules. About 0 are common, 6 are distinctive, and 4 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈6
Distinctive · estimate
This author's own choices. Worth a look.
4
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Very specific: line 15
Before /specify or /plan commands
- Very specific: line 40
Run scripts/scan-patterns.sh to auto-detect project stack before manual exploration.
- Very specific: line 52
Use WebSearch to survey the solution space (e.g.
- Very specific: line 57
Use WebFetch to read official docs, getting-started guides, and API references for each candidate
- Distinctive: line 62
Search for "[candidate] vs [candidate]" comparisons, benchmarks, and post-mortems
- Distinctive: line 63
Search for "[candidate] production issues" or "[candidate] limitations"
- Distinctive: line 64
Look for community size indicators: GitHub stars, npm weekly downloads, Stack Overflow activity
- Distinctive: line 67
Check compatibility with the project's detected stack (from Phase 1)
- Distinctive: line 68
Search for "[candidate] + [framework]" integration guides
- Distinctive: line 131
Use the ask question tool when research reveals multiple valid approaches
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
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
/specifyor/plancommands - 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
- Existing patterns — how similar problems are solved
- Reusable components — what can be leveraged
- Conventions — naming, structure, architecture patterns
- Dependencies — libraries/frameworks in use
Run scripts/scan-patterns.sh to auto-detect project stack before manual exploration.
Phase 2: External Solutions (Standard)
- Best practices — industry standards for this problem
- Library options — available tools and tradeoffs
- 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
WebSearchto 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
WebFetchto 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
- Compare options — pros/cons matrix with weighted criteria
- Recommend approach — based on findings, with confidence level
- Flag risks — technical concerns and unknowns
- 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 patternsreferences/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
/specifyandsdd-plannersubagent - Can be invoked by
sdd-explorerfor deeper analysis - Use the ask question tool when research reveals multiple valid approaches
- Deep research mode uses
WebSearchandWebFetchtools extensively — ensure sandbox allows outbound access
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