Agent skill

In Depth Research Guide

by wentorai in wentorai/research-plugins

Structured methodology for conducting exhaustive multi-source investigations

MITAuto-check passedResearch & Science

Install In Depth Research Guide

skills CLI
$ npx skills add wentorai/research-plugins --skill in-depth-research-guide -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install wentorai/research-plugins in-depth-research-guide --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/wentorai/research-plugins.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/research/deep-research/in-depth-research-guide .claude/skills/in-depth-research-guide && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
in-depth-research-guide
GitHub stars
298
Used in
1 other repo
Token cost
~1.9k tokens
SKILL.md length
468 words
Files
1
Skills in repo
405
Repo updated
First seen
Licence
MIT

At a glance

Structured methodology for conducting exhaustive multi-source investigations

  • Works in 5 steps: Scope Definition (10% of effort) → Multi-Source Collection (30% of effort) → Source Evaluation (20% of effort) → …
  • Tasks that involve Deep research
  • SKILL.md covers Overview, The 5-Phase Investigation…, Iteration Protocol and Quality Indicators, plus 1 more section
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

In Depth Research Guide is an agent skill from wentorai/research-plugins. Structured methodology for conducting exhaustive multi-source investigations

Its SKILL.md is about 1.9k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Research & Science, covering Deep research. The repository describes itself as: 350+ academic research skills, MCP configs, and plugins for Research-Claw and AI agents. The licence is MIT.

When your agent uses it

  • Tasks that involve Deep research

Example prompts

  • “/in-depth-research-guide”

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Scope Definition (10% of effort)
  2. Multi-Source Collection (30% of effort)
  3. Source Evaluation (20% of effort)
  4. Evidence Synthesis (30% of effort)
  5. Deliverable Production (10% of effort)

What it can do on your machine

Read from SKILL.md and the folder at commit bf44b3c. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

In Depth Research Guide loads about 1.9k tokens when it runs. Until then it costs about 25 tokens; SKILL.md has 468 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~25
When it runs · the whole SKILL.md, loaded when a task matches
~1.9k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from wentorai/research-plugins at commit bf44b3c, republished under its MIT licence (© wentorai). 468 words, ~1,936 tokens.

Download SKILL.mdSave it as .claude/skills/in-depth-research-guide/SKILL.md (or your agent's skills folder).
name
in-depth-research-guide
description
Structured methodology for conducting exhaustive multi-source investigations

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:

TierSource TypeExamplesPurpose
1Academic databasesOpenAlex, PubMed, Scopus, Web of SciencePeer-reviewed primary research
2Preprint serversarXiv, bioRxiv, SSRN, medRxivCutting-edge, not yet reviewed
3Grey literatureWHO reports, World Bank, NBER working papersPolicy and institutional knowledge
4Patents and standardsGoogle Patents, USPTO, IEEE standardsTechnical implementations
5Data repositoriesZenodo, Figshare, Kaggle, ICPSRRaw data and reproducibility
6Expert knowledgeConference talks, interviews, personal communicationTacit 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
FindingSource(s)Evidence LevelStrengthNotes
LLMs improve code quality by 20-40%[A], [B], [C]Level 2-3Strong (convergent)Effect varies by task complexity
Developers trust AI suggestions less for security-critical code[D], [E]Level 4ModerateSmall sample sizes
No significant effect on debugging time[F]Level 2Weak (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
Show full SKILL.md (199 more words)Show less
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 summaries)
  3. Identify gaps explicitly ("No studies have examined...")
  4. State implications for your research

For a State-of-the-Art Report:

  1. Current landscape with taxonomy
  2. Key advances and timelines
  3. Open problems and active debates
  4. Future directions with evidence basis

For a Policy Brief:

  1. Executive summary (1 paragraph)
  2. Evidence summary (1-2 pages)
  3. Policy options with trade-offs
  4. Recommended action with justification

Iteration Protocol

Deep research is inherently iterative. After Phase 4, reassess:

After synthesis:
  □ Are all sub-questions adequately answered?
  □ Are there new sub-questions that emerged?
  □ Are there critical gaps requiring additional search?
  □ Are contradictions resolved or at least documented?

If gaps remain:
  → Return to Phase 2 with refined queries
  → Maximum 3 iteration cycles before declaring scope complete
  → Document what remains unknown (future work)

Quality Indicators

A well-executed in-depth investigation should demonstrate:

  • Breadth: Multiple source tiers consulted (not just Google Scholar)
  • Depth: Key papers read in full, not just abstracts
  • Rigor: Evidence levels assessed, contradictions documented
  • Transparency: Search strategy reproducible, decisions justified
  • Currency: Most recent relevant work included
  • Balance: Competing viewpoints represented fairly

References

  • Petticrew, M., & Roberts, H. (2006). Systematic Reviews in the Social Sciences. Blackwell.
  • Grant, M. J., & Booth, A. (2009). "A typology of reviews." Health Information & Libraries Journal, 26(2), 91-108.
  • Snyder, H. (2019). "Literature review as a research methodology." Journal of Business Research, 104, 333-339.

© wentorai, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/research/deep-research/in-depth-research-guide of wentorai/research-plugins.

Open the folder on GitHubat commit bf44b3c

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in wentorai/research-plugins, which our catalogue first saw on October 7, 2026.

Compare with similar skills

In Depth Research Guide next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

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Deep Research WorkflowTokenRhythm/opensquilla7.1k—~1.3kAutomated safety check: PassApache-2.0
Deep Researchsanjay3290/ai-skills4329 repos~683Automated safety check: NotesApache-2.0
Horizontal-Vertical Deep ResearchKKKKhazix/khazix-skills21k—~2.1kAutomated safety check: PassMIT
Academic Research PipelineImbad0202/academic-research-skills51k—~15kAutomated safety check: PassCustom licence

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Questions about In Depth Research Guide

What does In Depth Research Guide do?

Structured methodology for conducting exhaustive multi-source investigations. In Depth Research Guide is an agent skill from wentorai/research-plugins.

When should I use In Depth Research Guide?

In Depth Research Guide fits situations like: tasks that involve Deep research.

How do I install In Depth Research Guide in Claude Code?

Run `npx skills add wentorai/research-plugins --skill in-depth-research-guide -a claude-code`. Or copy the skill folder (skills/research/deep-research/in-depth-research-guide in wentorai/research-plugins) into .claude/skills/in-depth-research-guide in your project. Claude Code loads it when a task matches its description.

How do I install In Depth Research Guide in Codex?

Run `npx skills add wentorai/research-plugins --skill in-depth-research-guide -a codex`. Or copy the skill folder (skills/research/deep-research/in-depth-research-guide in wentorai/research-plugins) into .agents/skills/in-depth-research-guide in your project. Codex loads it when a task matches its description.

Can I use In Depth Research Guide in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add wentorai/research-plugins --skill in-depth-research-guide -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/in-depth-research-guide, .gemini/skills/in-depth-research-guide, .github/skills/in-depth-research-guide and .opencode/skills/in-depth-research-guide in your project.

What does In Depth Research Guide need to run?

SKILL.md names no scripts, command-line tools or credentials: In Depth Research Guide is instructions for the agent only.

Does In Depth Research Guide access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is In Depth Research Guide safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does In Depth Research Guide use?

In Depth Research Guide is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does In Depth Research Guide use?

About 1.9k tokens (SKILL.md is roughly 7.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to In Depth Research Guide?

Skills that share tags, products or a category with In Depth Research Guide: GitHub Deep Research (bytedance/deer-flow, 84k stars), Deep Research Workflow (TokenRhythm/opensquilla, 7.1k stars), Deep Research (sanjay3290/ai-skills, 432 stars) and Horizontal-Vertical Deep Research (KKKKhazix/khazix-skills, 21k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains In Depth Research Guide?

wentorai (a GitHub user) maintains it in wentorai/research-plugins, which has 298 GitHub stars. The repository holds 405 skills in this directory. The repository was last updated on June 19, 2026.

Source: wentorai/research-plugins on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.