/nw-research-methodology
Research output templates, distillation workflow, and quality standards for evidence-driven research
Claude Code
$ npx -y skills add nWave-ai/nWave --skill nw-research-methodology --agent claude-code
Codex
$ npx skills add nWave-ai/nWave --skill nw-research-methodology -a codex -y
Cursor
$ npx skills add nWave-ai/nWave --skill nw-research-methodology -a cursor -y
Gemini CLI
$ npx skills add nWave-ai/nWave --skill nw-research-methodology -a gemini-cli -y
GitHub Copilot
$ npx skills add nWave-ai/nWave --skill nw-research-methodology -a github-copilot -y
OpenCode
$ npx skills add nWave-ai/nWave --skill nw-research-methodology -a opencode -y
Windsurf
$ npx skills add nWave-ai/nWave --skill nw-research-methodology -a windsurf -y
SKILL.md
nw-research-methodology.SKILL.mdname: nw-research-methodology
description: Research output templates, distillation workflow, and quality standards for evidence-driven research
user-invocable: false
disable-model-invocation: true
Research Methodology
Research Output Template
Use for all research documents in `docs/research/`.
# Research: {Topic}
**Date**: {ISO-8601} | **Researcher**: nw-researcher (Nova) | **Confidence**: {High/Medium/Low} | **Sources**: {count}
## Executive Summary
{2-3 paragraph overview of key findings, main insights, and overall conclusion}
## Research Methodology
**Search Strategy**: {how sources were found}
**Source Selection**: Types: {academic/official/industry/technical_docs} | Reputation: {high/medium-high min} | Verification: {cross-referencing approach}
**Quality Standards**: Target 3 sources/claim (min 1 authoritative) | All major claims cross-referenced | Avg reputation: {0.0-1.0}
## Findings
### Finding 1: {Descriptive Title}
**Evidence**: "{Direct quote or specific data point}"
**Source**: [{Source Name}]({URL}) - Accessed {YYYY-MM-DD}
**Confidence**: {High/Medium/Low}
**Verification**: [{Source 2}]({URL2}), [{Source 3}]({URL3})
**Analysis**: {Brief interpretation or context}
{Repeat Finding structure as needed}
## Source Analysis
| Source | Domain | Reputation | Type | Access Date | Cross-verified |
|--------|--------|------------|------|-------------|----------------|
| {name} | {domain} | {High/Medium-High/Medium} | {academic/official/industry/technical} | {YYYY-MM-DD} | {Y/N} |
Reputation: High: {count} ({%}) | Medium-high: {count} ({%}) | Avg: {0.0-1.0}
## Knowledge Gaps
### Gap 1: {Description}
**Issue**: {missing/unclear info} | **Attempted**: {sources searched} | **Recommendation**: {how to address}
## Conflicting Information (if applicable)
### Conflict 1: {Topic}
**Position A**: {Statement} — Source: [{Name}]({URL}), Reputation: {score}, Evidence: {quote}
**Position B**: {Contradictory statement} — Source: [{Name}]({URL}), Reputation: {score}, Evidence: {quote}
**Assessment**: {Which source more authoritative and why}
## Recommendations for Further Research
1. {Specific recommendation with rationale}
## Full Citations
[1] {Author}. "{Title}". {Publication}. {Date}. {URL}. Accessed {YYYY-MM-DD}.
## Research Metadata
Duration: {X min} | Examined: {count} | Cited: {count} | Cross-refs: {count} | Confidence: High {%}, Medium {%}, Low {%} | Output: docs/research/{filename}Skill Distillation Workflow
When creating a skill (via `*create-skill` or `skill_for` specified):
Phase 1: Research
Execute comprehensive research, create full doc in `docs/research/{category}/{topic}-comprehensive-research.md`, complete quality gates.
Phase 2: Distillation
1. Read comprehensive research 2. Transform: academic -> practitioner-focused 3. Preserve 100% essential concepts (no lossy compression) 4. Remove: verbose explanations, extensive examples, redundant cross-refs 5. Keep: core concepts, practical tools, methodologies, decision heuristics 6. Make self-contained (no external refs) | Target <1000 tokens/file 7. Write to `~/.claude/skills/nw-{skill-name}/SKILL.md{topic}-methodology.md`
Phase 3: Validation
Verify all essential concepts present | Confirm practitioner focus | Check self-containment
Quality Standards
Per-Claim Requirements (Adaptive to Turn Budget)
Source requirements adapt to available turn budget:
- **Ideal**: 3+ independent sources per major claim
- **Acceptable**: 2 credible sources when budget is constrained
- **Minimum**: 1 authoritative source (official docs, RFC, specification) with explicit confidence note
- **Never**: 0 sources -- unsourced claims must be flagged as "[unverified]"
When budget runs low, prioritize BREADTH (cover all claims with minimum sources) over DEPTH (exhaust sources for one claim while ignoring others).
Additional requirements:
- Each source validated against trusted source config from prompt context
- Cross-reference status documented per finding
Confidence Ratings
- **High**: 3+ high-reputation sources agree, no contradictions
- **Medium**: 2+ agree, minor contradictions or some medium-trust
- **Low**: single source or significant contradictions
Quality Gates (before finalizing)
1. Every major claim has citations (3+ ideal, 2 acceptable, 1 authoritative minimum) | 2. All sources from trusted domains 3. All findings evidence-backed | 4. Knowledge gaps documented | 5. Output in allowed directories 6. Claims with fewer than 3 sources have confidence rating adjusted accordingly
Read more
name: nw-research-methodology description: Research output templates, distillation workflow, and quality standards for evidence-driven research user-invocable: false disable-model-invocation: true
Research Methodology
Research Output Template
Use for all research documents in `docs/research/`.
# Research: {Topic}
**Date**: {ISO-8601} | **Researcher**: nw-researcher (Nova) | **Confidence**: {High/Medium/Low} | **Sources**: {count}
## Executive Summary
{2-3 paragraph overview of key findings, main insights, and overall conclusion}
## Research Methodology
**Search Strategy**: {how sources were found}
**Source Selection**: Types: {academic/official/industry/technical_docs} | Reputation: {high/medium-high min} | Verification: {cross-referencing approach}
**Quality Standards**: Target 3 sources/claim (min 1 authoritative) | All major claims cross-referenced | Avg reputation: {0.0-1.0}
## Findings
### Finding 1: {Descriptive Title}
**Evidence**: "{Direct quote or specific data point}"
**Source**: [{Source Name}]({URL}) - Accessed {YYYY-MM-DD}
**Confidence**: {High/Medium/Low}
**Verification**: [{Source 2}]({URL2}), [{Source 3}]({URL3})
**Analysis**: {Brief interpretation or context}
{Repeat Finding structure as needed}
## Source Analysis
| Source | Domain | Reputation | Type | Access Date | Cross-verified |
|--------|--------|------------|------|-------------|----------------|
| {name} | {domain} | {High/Medium-High/Medium} | {academic/official/industry/technical} | {YYYY-MM-DD} | {Y/N} |
Reputation: High: {count} ({%}) | Medium-high: {count} ({%}) | Avg: {0.0-1.0}
## Knowledge Gaps
### Gap 1: {Description}
**Issue**: {missing/unclear info} | **Attempted**: {sources searched} | **Recommendation**: {how to address}
## Conflicting Information (if applicable)
### Conflict 1: {Topic}
**Position A**: {Statement} — Source: [{Name}]({URL}), Reputation: {score}, Evidence: {quote}
**Position B**: {Contradictory statement} — Source: [{Name}]({URL}), Reputation: {score}, Evidence: {quote}
**Assessment**: {Which source more authoritative and why}
## Recommendations for Further Research
1. {Specific recommendation with rationale}
## Full Citations
[1] {Author}. "{Title}". {Publication}. {Date}. {URL}. Accessed {YYYY-MM-DD}.
## Research Metadata
Duration: {X min} | Examined: {count} | Cited: {count} | Cross-refs: {count} | Confidence: High {%}, Medium {%}, Low {%} | Output: docs/research/{filename}Skill Distillation Workflow
When creating a skill (via `*create-skill` or `skill_for` specified):
Phase 1: Research
Execute comprehensive research, create full doc in `docs/research/{category}/{topic}-comprehensive-research.md`, complete quality gates.
Phase 2: Distillation
1. Read comprehensive research 2. Transform: academic -> practitioner-focused 3. Preserve 100% essential concepts (no lossy compression) 4. Remove: verbose explanations, extensive examples, redundant cross-refs 5. Keep: core concepts, practical tools, methodologies, decision heuristics 6. Make self-contained (no external refs) | Target <1000 tokens/file 7. Write to `~/.claude/skills/nw-{skill-name}/SKILL.md{topic}-methodology.md`
Phase 3: Validation
Verify all essential concepts present | Confirm practitioner focus | Check self-containment
Quality Standards
Per-Claim Requirements (Adaptive to Turn Budget)
Source requirements adapt to available turn budget:
- **Ideal**: 3+ independent sources per major claim
- **Acceptable**: 2 credible sources when budget is constrained
- **Minimum**: 1 authoritative source (official docs, RFC, specification) with explicit confidence note
- **Never**: 0 sources -- unsourced claims must be flagged as "[unverified]"
When budget runs low, prioritize BREADTH (cover all claims with minimum sources) over DEPTH (exhaust sources for one claim while ignoring others).
Additional requirements:
- Each source validated against trusted source config from prompt context
- Cross-reference status documented per finding
Confidence Ratings
- **High**: 3+ high-reputation sources agree, no contradictions
- **Medium**: 2+ agree, minor contradictions or some medium-trust
- **Low**: single source or significant contradictions
Quality Gates (before finalizing)
1. Every major claim has citations (3+ ideal, 2 acceptable, 1 authoritative minimum) | 2. All sources from trusted domains 3. All findings evidence-backed | 4. Knowledge gaps documented | 5. Output in allowed directories 6. Claims with fewer than 3 sources have confidence rating adjusted accordingly
AI agents that guide you from idea to working code, with human judgment at every gate. nWave runs inside Claude Code. It breaks feature delivery into seven waves (discover, diverge, discuss, design, devops, distill, deliver).
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Questions about nw-research-methodology.
- Which coding agents can use nw-research-methodology?
- nw-research-methodology installs in Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode and Windsurf with the skills CLI, using each agent's flag shown on this page. Flowy's auto-invocation, which fires a skill when your prompt matches, runs in Claude Code only.

