Agent skill

Mixed Methods Guide

by wentorai in wentorai/research-plugins

Guide to designing and conducting mixed methods research. An agent skill from wentorai/research-plugins.

MITAuto-check passedResearch & Science

Install Mixed Methods Guide

skills CLI
$ npx skills add wentorai/research-plugins --skill mixed-methods-guide -a claude-code

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

GitHub CLI
$ gh skill install wentorai/research-plugins mixed-methods-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/methodology/mixed-methods-guide .claude/skills/mixed-methods-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
mixed-methods-guide
GitHub stars
298
Used in
1 other repo
Token cost
~2.2k tokens
SKILL.md length
644 words
Files
1
Skills in repo
405
Repo updated
First seen
Licence
MIT

At a glance

Guide to designing and conducting mixed methods research. An agent skill from wentorai/research-plugins.

  • Works in 7 steps: Research questions: State both QUAN and… → Design rationale: Explain why mixed… → Design type: Name the specific design… → …
  • Research & Science work in your project
  • SKILL.md covers What Is Mixed Methods Research?, Major Mixed Methods Designs, Integration Strategies and Sample Size Considerations, plus 2 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Mixed Methods Guide is an agent skill from wentorai/research-plugins. Guide to designing and conducting mixed methods research

Its SKILL.md is about 2.2k 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. 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

  • Research & Science work in your project

Example prompts

  • “/mixed-methods-guide”

Requirements

  • Python 3

Workflow steps

7 steps, taken from the first numbered list in SKILL.md.

  1. Research questions: State both QUAN and QUAL questions plus the mixed methods question
  2. Design rationale: Explain why mixed methods is needed
  3. Design type: Name the specific design (convergent, explanatory sequential, etc.)
  4. Strand descriptions: Describe each strand's methods in detail
  5. Integration procedure: Explain how and when data are integrated
  6. Joint display: Present integrated findings in a table or figure
  7. Meta-inferences: Draw conclusions that leverage both data types

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 python).

    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

Mixed Methods Guide loads about 2.2k tokens when it runs. Until then it costs about 19 tokens; SKILL.md has 644 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~19
When it runs · the whole SKILL.md, loaded when a task matches
~2.2k

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). 644 words, ~2,215 tokens.

Download SKILL.mdSave it as .claude/skills/mixed-methods-guide/SKILL.md (or your agent's skills folder).
name
mixed-methods-guide
description
Guide to designing and conducting mixed methods research

Mixed Methods Research Guide

Design, execute, and report mixed methods research that integrates quantitative and qualitative approaches for more comprehensive and rigorous findings.

What Is Mixed Methods Research?

Mixed methods research (MMR) systematically combines quantitative and qualitative data collection, analysis, and interpretation within a single study or program of inquiry. It goes beyond simply using both numbers and words; the core requirement is purposeful integration of the two strands.

When to Use Mixed Methods
SituationWhy MMR Helps
Quantitative results need explanationQualitative follow-up explains why and how
Need to develop an instrumentQualitative exploration informs survey items
Testing a new interventionQuantitative outcomes + qualitative experience
Complex phenomenaNeither approach alone captures the full picture
Conflicting prior findingsTriangulation resolves discrepancies
Studying under-researched topicsExploration (qual) then confirmation (quant)

Major Mixed Methods Designs

Convergent Design (Concurrent)

Both strands are collected simultaneously, analyzed separately, then merged.

    QUAN data collection          QUAL data collection
           |                              |
    QUAN data analysis            QUAL data analysis
           |                              |
           +---------- Merge ------------+
                         |
                  Interpretation

Use when: You want to compare, validate, or triangulate quantitative and qualitative findings on the same phenomenon.

Example: Survey 500 teachers on burnout (QUAN) while simultaneously interviewing 20 teachers about their experiences (QUAL). Merge findings to see if themes align with statistical patterns.

Explanatory Sequential Design

Quantitative phase first, followed by qualitative phase to explain or elaborate on quantitative results.

    QUAN data collection & analysis
                |
    Identify results needing explanation
                |
    QUAL data collection & analysis (informed by QUAN results)
                |
           Interpretation

Use when: You have surprising, confusing, or significant quantitative results that need deeper understanding.

Example: Find that 30% of participants show an unexpected improvement pattern. Interview those participants to understand what drove their experience.

Exploratory Sequential Design

Qualitative phase first to explore, followed by quantitative phase to test or generalize.

    QUAL data collection & analysis
                |
    Develop instrument / hypotheses / categories from QUAL findings
                |
    QUAN data collection & analysis (testing QUAL-derived constructs)
                |
           Interpretation

Use when: You are studying something new and need qualitative exploration to develop measurement instruments or hypotheses.

Example: Interview 25 researchers about AI tool adoption (QUAL). Use themes to develop a survey instrument. Administer survey to 400 researchers (QUAN).

Embedded Design

One strand is embedded within the other, serving a supplementary role.

    QUAN experiment
        |-- Embedded QUAL (interviews during intervention)
        |-- QUAN outcome measures
           |
       Interpretation

Integration Strategies

Integration is what distinguishes mixed methods from simply running two separate studies. Key integration strategies:

StrategyDescriptionWhen in Study
MergingBring QUAN + QUAL results together for comparisonAnalysis/interpretation
ConnectingOne strand's results inform the next strand's designBetween phases
BuildingQUAL results build a QUAN instrument (or vice versa)Between phases
EmbeddingOne strand is nested within the other's frameworkData collection
Joint Display Table

A joint display is a table or visualization that explicitly integrates both data types:

| Quantitative Finding | Qualitative Theme | Meta-Inference |
|---------------------|-------------------|----------------|
| 78% reported high stress (M=4.2/5) | Theme: "Always-on culture" — participants described checking email at midnight | Convergent: high stress scores align with descriptions of boundary erosion |
| No significant gender difference (p=.34) | Women described unique stressors (caregiving + work), men described different ones (promotion pressure) | Divergent: similar overall levels but different sources of stress |
| Time-management training reduced stress (d=0.45) | Theme: "Tools help but culture doesn't change" | Complementary: training has modest measurable effect but underlying issues persist |
Show full SKILL.md (255 more words)Show less

Sample Size Considerations

StrandTypical RangeRationale
Quantitative (survey)100-1000+Power analysis, see power-analysis-guide
Qualitative (interviews)12-30Saturation (no new themes emerging)
Qualitative (focus groups)3-6 groups of 6-10Diversity of perspectives
Qualitative (case study)3-10 casesIn-depth understanding

For convergent designs: The QUAN sample is typically much larger than the QUAL sample. This is acceptable because the two strands serve different purposes (generalizability vs. depth).

Data Analysis

Quantitative Analysis

Standard statistical methods apply: descriptive statistics, t-tests, ANOVA, regression, SEM, etc. See the relevant analysis skill guides.

Qualitative Analysis

Common approaches:

1. Thematic Analysis (Braun & Clarke, 2006)
   Step 1: Familiarize with data (read transcripts multiple times)
   Step 2: Generate initial codes
   Step 3: Search for themes (group codes into higher-level themes)
   Step 4: Review themes (check against data)
   Step 5: Define and name themes
   Step 6: Write up findings

2. Coding Process:
   - Open coding: label meaningful segments of text
   - Axial coding: identify relationships between codes
   - Selective coding: identify core categories

3. Tools: NVivo, ATLAS.ti, MAXQDA, Dedoose, or manual coding in spreadsheets
Integration Analysis
python
# Example: Quantifying qualitative themes for integration
import pandas as pd

# After coding interviews, create a themes-by-participant matrix
themes_matrix = pd.DataFrame({
    "participant": ["P01", "P02", "P03", "P04", "P05"],
    "high_stress": [1, 1, 0, 1, 1],      # 1 = theme present
    "boundary_erosion": [1, 0, 0, 1, 1],
    "coping_strategy": [0, 1, 1, 1, 0],
    "quant_stress_score": [4.5, 3.8, 2.1, 4.2, 4.0]
})

# Now examine whether theme presence correlates with quantitative scores
from scipy.stats import pointbiserialr

r, p = pointbiserialr(themes_matrix["high_stress"],
                       themes_matrix["quant_stress_score"])
print(f"Correlation between stress theme and score: r={r:.3f}, p={p:.3f}")

Reporting Mixed Methods Research

Essential Components
  1. Research questions: State both QUAN and QUAL questions plus the mixed methods question
  2. Design rationale: Explain why mixed methods is needed
  3. Design type: Name the specific design (convergent, explanatory sequential, etc.)
  4. Strand descriptions: Describe each strand's methods in detail
  5. Integration procedure: Explain how and when data are integrated
  6. Joint display: Present integrated findings in a table or figure
  7. Meta-inferences: Draw conclusions that leverage both data types
Quality Criteria
CriterionQuantitativeQualitativeMixed Methods
ValidityInternal, external, construct, statistical conclusionCredibility, transferability, dependability, confirmabilityInference quality, inference transferability
ReliabilityCronbach's alpha, test-retestIntercoder agreement, audit trailIntegration consistency
RigorRandomization, control, blindingProlonged engagement, member checking, triangulationDesign coherence, integrative adequacy
  • APA JARS-Mixed (Journal Article Reporting Standards for Mixed Methods)
  • O'Cathain et al. (2008) Good Reporting of a Mixed Methods Study (GRAMMS)
  • Creswell & Plano Clark (2018) Designing and Conducting Mixed Methods Research, 3rd Edition (the standard textbook)

© 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/methodology/mixed-methods-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

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Questions about Mixed Methods Guide

What does Mixed Methods Guide do?

Guide to designing and conducting mixed methods research. An agent skill from wentorai/research-plugins. Mixed Methods Guide is an agent skill from wentorai/research-plugins.

When should I use Mixed Methods Guide?

Mixed Methods Guide fits situations like: research & Science work in your project.

How do I install Mixed Methods Guide in Claude Code?

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

How do I install Mixed Methods Guide in Codex?

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

Can I use Mixed Methods 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 mixed-methods-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/mixed-methods-guide, .gemini/skills/mixed-methods-guide, .github/skills/mixed-methods-guide and .opencode/skills/mixed-methods-guide in your project.

What does Mixed Methods Guide need to run?

SKILL.md names no scripts, command-line tools or credentials: Mixed Methods Guide is instructions for the agent only. Our summary lists: Python 3.

Does Mixed Methods 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 Mixed Methods 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 Mixed Methods Guide use?

Mixed Methods 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 Mixed Methods Guide use?

About 2.2k tokens (SKILL.md is roughly 8.9k 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 Mixed Methods Guide?

Skills that share tags, products or a category with Mixed Methods Guide: Hypothesis Generation (spacering-net/codeg, 3.8k stars), GitHub Deep Research (bytedance/deer-flow, 83k stars), Nature Paper Card (Yuan1z0825/nature-skills, 46k stars) and Read arXiv Paper (karpathy/nanochat, 58k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Mixed Methods 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.