Atlas / Skills / brycewang-stanford / In Depth Research Guide

In Depth Research GuideSAFE

skills/brycewang-stanford/in-depth-research-guide

🔬 A curated collection of 23,000+ agent skills for empirical research across 8 social science disciplines. | 精选 23,000+ AI Agent 技能库,覆盖8大社会科学学科的实证研究。CoPaper.AI 20分钟完成一篇可复现的规范实证论文,并支持用户上传 Skills。-- Maintained by CoPaper.AI from Stanford REAP.

Verdict
SAFE
Grade
B
Trust score
89 /100
Version
—
Hosts
1 documented
License
NOASSERTION
Stars
4,537
01

Overview

🔬 A curated collection of 23,000+ agent skills for empirical research across 8 social science disciplines. | 精选 23,000+ AI Agent 技能库,覆盖8大社会科学学科的实证研究。CoPaper.AI 20分钟完成一篇可复现的规范实证论文,并支持用户上传 Skills。-- Maintained by CoPaper.AI from Stanford REAP.

Read from source at commit e1ba289846fdOBSERVED · 2026-10-08
02

Host compatibility

What the documentation claims. We have not run a compatibility test.

HostStatusNotes
openclawmentioned
03

What it tells the agent

The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.

---
name: in-depth-research-guide
description: "Structured methodology for conducting exhaustive multi-source investigations"
metadata:
  openclaw:
    emoji: "🔬"
    category: "research"
    subcategory: "deep-research"
    keywords: ["deep research", "systematic investigation", "multi-source research", "evidence synthesis", "research methodology", "source evaluation"]
    source: "wentor-research-plugins"
---

# In-Depth Research Methodology

## Overview

In-depth research goes beyond surface-level literature review to conduct exhaustive, multi-source investigations that synthesize evidence from academic papers, grey literature, industry reports, datasets, and primary sources. This methodology is used when a research question requires comprehensive coverage — for systematic reviews, policy briefs, competitive analyses, or foundational literature surveys in a new research direction.

## The 5-Phase Investigation Framework

### Phase 1: Scope Definition (10% of effort)

Before searching, define boundaries explicitly:

```markdown
## Research Brief Template

**Central Question**: [One sentence, specific and falsifiable]
**Sub-Questions** (3-5):
  1. [Decomposed aspect 1]
  2. [Decomposed aspect 2]
  3. [Decomposed aspect 3]

**Inclusion Criteria**:
  - Time range: [e.g., 2018-present]
  - Languages: [e.g., English, Chinese]
  - Document types: [peer-reviewed, preprints, reports, patents]
  - Disciplines: [e.g., CS, cognitive science, linguistics]

**Exclusion Criteria**:
  - [Opinion pieces, blog posts without data]
  - [Studies with n < 30 unless qualitative]
  - [Duplicate publications of same study]

**Expected Deliverable**: [Literature review / Evidence map / Policy brief / State-of-art report]
**Depth Target**: [Exhaustive / Representative / Exploratory]
```

### Phase 2: Multi-Source Collection (30% of effort)

Search systematically across source tiers:

| Tier | Source Type | Examples | Purpose |
|------|-----------|---------|---------|
| **1** | Academic databases | OpenAlex, PubMed, Scopus, Web of Science | Peer-reviewed primary research |
| **2** | Preprint servers | arXiv, bioRxiv, SSRN, medRxiv | Cutting-edge, not yet reviewed |
| **3** | Grey literature | WHO reports, World Bank, NBER working papers | Policy and institutional knowledge |
| **4** | Patents and standards | Google Patents, USPTO, IEEE standards | Technical implementations |
| **5** | Data repositories | Zenodo, Figshare, Kaggle, ICPSR | Raw data and reproducibility |
| **6** | Expert knowledge | Conference talks, interviews, personal communication | Tacit knowledge, emerging trends |

**Search strategy per source**:

```markdown
For each source:
1. Construct 3-5 query variants (synonyms, related terms, translated terms)
2. Apply inclusion/exclusion filters
3. Record: query string, date, results count, relevant hits
4. Download and tag all relevant items
5. Snowball: check references of key papers (backward) and citing papers (forward)
```

### Phase 3: Source Evaluation (20% of effort)

Rate each source on a standardized evidence hierarchy:

```
Level 1: Systematic reviews and meta-analyses
Level 2: Randomized controlled trials / controlled experiments
Level 3: Cohort studies / quasi-experimental designs
Level 4: Case-control studies / cross-sectional surveys
Level 5: Case reports / case series / expert opinion
Level 6: Anecdotal evidence / grey literature without methodology
```

**Credibility checklist per source**:

```markdown
□ Author credentials and affiliation
□ Publication venue (impact factor, peer-review process)
□ Methodology transparency (can you replicate it?)
□ Sample size and representativeness
□ Conflict of interest disclosure
□ Recency (is the data still relevant?)
□ Citation count and reception (supportive vs. critical citations)
□ Consistency with other sources (does it converge or contradict?)
```

### Phase 4: Evidence Synthesis (30% of effort)

Organize findings into structured artifacts:

#### Evidence Matrix

| Finding | Source(s) | Evidence Level | Strength | Notes |
|---------|-----------|---------------|----------|-------|
| LLMs improve code quality by 20-40% | [A], [B], [C] | Level 2-3 | Strong (convergent) | Effect varies by task complexity |
| Developers trust AI suggestions less for security-critical code | [D], [E] | Level 4 | Moderate | Small sample sizes |
| No significant effect on debugging time | [F] | Level 2 | Weak (single study) | Contradicts [A] — needs reconciliation |

#### Contradiction Log

When sources disagree, document systematically:

```markdown
## Contradiction: Effect of X on Y

**Position A**: X increases Y (Smith 2023, Jones 2024)
  - Evidence: RCT with n=500, effect size d=0.4
  - Context: University students, controlled setting

**Position B**: X has no effect on Y (Lee 2024)
  - Evidence: Field study with n=1200, p=0.34
  - Context: Industry practitioners, naturalistic setting

**Resolution hypothesis**: The effect is moderated by expertise level.
  Position A's sample (students) shows the effect;
  Position B's sample (practitioners) does not.
  → Need: Study that measures expertise as a moderator.
```

#### Knowledge Map

Visualize the landscape of your findings:

```
Central Question
├── Sub-Q1: [Strong evidence — 8 sources, convergent]
│   ├── Finding 1.1 (Level 2, 3 sources)
│   ├── Finding 1.2 (Level 3, 2 sources)
│   └── Finding 1.3 (Level 4, 3 sources)
├── Sub-Q2: [Mixed evidence — 5 sources, 1 contradiction]
│   ├── Finding 2.1 (Level 2, 2 sources)
│   └── Finding 2.2 ⚠️ CONTRADICTED by Finding 2.3
├── Sub-Q3: [Weak evidence — 2 sources, emerging area]
│   └── Finding 3.1 (Level 5, 2 sources)
└── Unexpected: [Theme that emerged during research]
    └── Finding 4.1 (Level 3, 1 source) → needs further investigation
```

### Phase 5: Deliverable Production (10% of effort)

Compile findings into the target deliverable format:

**For a Literature Review**:
1. Organize by themes (not chronologically)
2. Synthesize across sources (not paper-by-paper su
04

Trust audit

SAFEgrade B · trust 89/100 Nothing in the source contradicts what it says it does. Grade A is reserved for packages that have also passed the behavioural sandbox.

LayerWhat it checksResult
L0Provenance & inventoryPASS
L1Static analysis of the codeNA
L2Instruction surface (what it tells the agent)PASS
L3Class-specific surfacePASS
L4Behavioural (sandbox)SKIPPED

What the source does

Filesystem
none-observed
Network
none-observed
Shell
none-observed
Dependencies
pinned
Secrets in source
none-found

Findings (0)

No findings outside the package's declared scope.

Gates applied: no_behavioural_pass.

Audited 2026-10-08 · audit v0.4.1 · source sha e1ba289846fdfull audit observations/trust-audit/skill/brycewang-stanford__in-depth-research-guide.json · Report an issue / request a re-scan
05

Audit history

Every audit this skill has had.

DateSourceVerdictGradeScoreChange
2026-10-08e1ba289846fdSAFEB89first audit
06

Questions

What does the In Depth Research Guide skill do?

🔬 A curated collection of 23,000+ agent skills for empirical research across 8 social science disciplines. | 精选 23,000+ AI Agent 技能库,覆盖8大社会科学学科的实证研究。CoPaper.AI 20分钟完成一篇可复现的规范实证论文,并支持用户上传 Skills。-- Maintained by CoPaper.AI from Stanford REAP.

Is In Depth Research Guide safe to install?

The audit found nothing in the source that contradicts what it says it does, and graded it B (89/100). Grade A is held back for packages that have also passed a sandboxed behavioural run, which is why a clean skill reads B.

What can In Depth Research Guide access on my machine?

The audit observed no filesystem, network or shell use at all in its source.

Which assistants does In Depth Research Guide work with?

Its documentation mentions openclaw. That is what the text claims, not a compatibility test we ran.

How current is this page?

The grade is for one exact copy of the source (e1ba289846fd), read on 2026-10-08. The repository is watched, and a new audit runs when it changes — this is the first audit.

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