instrument-data-to-all…
Convert laboratory instrument output files (PDF, CSV, Excel, TXT) to Allotrope Simple Model (ASM) JSON format or flattened 2D CSV. Use this skill when…
Synthesize user research from interviews, surveys, and feedback into structured insights. Use when you have a pile of interview notes, survey responses, or support tickets to make sense of, need to extract themes and rank findings by frequency and impact, or want to turn raw
$ npx -y skills add anthropics/knowledge-work-plugins --skill synthesize-research --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/synthesize-researchContext preview
The summary Claude sees to decide when to auto-load this skill.
Synthesize user research from interviews, surveys, and feedback into structured insights. Use when you have a pile of interview notes, survey responses, or support tickets to make sense of, need to extract themes and rank findings by frequency and impact, or want to turn raw
name: synthesize-research description: Synthesize user research from interviews, surveys, and feedback into structured insights. Use when you have a pile of interview notes, survey responses, or support tickets to make sense of, need to extract themes and rank findings by frequency and impact, or want to turn raw feedback into roadmap recommendations. argument-hint: "<research topic or question>"
> If you see unfamiliar placeholders or need to check which tools are connected, see [CONNECTORS.md](../../CONNECTORS.md).
Synthesize user research from multiple sources into structured insights and recommendations.
/synthesize-research $ARGUMENTS
Accept research from any combination of:
Ask the user what they have:
For each source, extract:
Apply thematic analysis — see **Research Synthesis Methodology** below for detailed guidance on thematic analysis, affinity mapping, and triangulation techniques.
Group observations into themes, count frequency across participants, and assess impact severity. Note contradictions and surprises.
Create a priority matrix:
Produce a structured research synthesis:
For each major finding (aim for 5-8):
Order findings by priority (frequency x impact).
If the research reveals distinct user segments:
Based on the findings, identify opportunity areas:
Specific, actionable recommendations:
What the research did not answer:
After generating the synthesis:
The core method for synthesizing qualitative research:
1. **Familiarization**: Read through all the data. Get a feel for the overall landscape before coding anything. 2. **Initial coding**: Go through the data systematically. Tag each observation, quote, or data point with descriptive codes. Be generous with codes — it is easier to merge than to split later. 3. **Theme development**: Group related codes into candidate themes. A theme captures something important about the data in relation to the research question. 4. **Theme review**: Check themes against the data. Does each theme have sufficient evidence? Are themes distinct from each other? Do they tell a coherent story? 5. **Theme refinement**: Define and name each theme clearly. Write a 1-2 sentence description of what each theme captures. 6. **Report**: Write up the themes as findings with supporting evidence.
A collaborative method for grouping observations:
1. **Capture observations**: Write each distinct observation, quote, or data point as a separate note 2. **Cluster**: Group related notes together based on similarity. Do not pre-define categories — let them emerge from the data. 3. **Label clusters**: Give each cluster a descriptive name that captures the common thread 4. **Organize clusters**: Arrange clusters into higher-level groups if patterns emerge 5. **Ident
Plugins that turn Claude into a specialist for your role, team, and company. Built for Claude Cowork, also compatible with Claude Code.
Repo: anthropics/knowledge-work-plugins
Convert laboratory instrument output files (PDF, CSV, Excel, TXT) to Allotrope Simple Model (ASM) JSON format or flattened 2D CSV. Use this skill when…
Run nf-core bioinformatics pipelines (rnaseq, sarek, atacseq) on sequencing data. Use when analyzing RNA-seq, WGS/WES, or ATAC-seq data—either local FASTQs or…
This skill should be used when scientists need help with research problem selection, project ideation, troubleshooting stuck projects, or strategic scientific…
Deep learning for single-cell analysis using scvi-tools. This skill should be used when users need (1) data integration and batch correction with scVI/scANVI,…
Performs quality control on single-cell RNA-seq data (.h5ad or .h5 files) using scverse best practices with MAD-based filtering and comprehensive…
Set up your bio-research environment and explore available tools. Use when first getting oriented with the plugin, checking which literature, drug-discovery,…