research-matrix-builder
Build literature matrices from papers, notes, and abstracts to compare methods, data, findings, and research gaps.
Best use case
research-matrix-builder is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Build literature matrices from papers, notes, and abstracts to compare methods, data, findings, and research gaps.
Teams using research-matrix-builder should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/research-matrix-builder/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How research-matrix-builder Compares
| Feature / Agent | research-matrix-builder | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Build literature matrices from papers, notes, and abstracts to compare methods, data, findings, and research gaps.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# Research Matrix Builder
## Purpose
Build literature matrices from papers, notes, and abstracts to compare methods, data, findings, and research gaps.
## Trigger phrases
- 文献矩阵
- build a literature matrix
- 整理论文综述
- research gap table
- 做研究对比表
## Ask for these inputs
- paper list or notes
- research question
- matrix dimensions
- citation style if needed
## Workflow
1. Normalize each source into the bundled matrix schema.
2. Extract problem, method, data, metric, result, limitation, and gap.
3. Cluster similar methods and contradictory findings.
4. Generate a matrix CSV and a narrative synthesis outline.
5. Keep missing fields explicit and cite where possible.
## Output contract
- literature matrix CSV
- thematic clusters
- gap summary
- review outline
## Files in this skill
- Script: `{baseDir}/scripts/build_matrix.py`
- Resource: `{baseDir}/resources/matrix_schema.csv`
## Operating rules
- Be concrete and action-oriented.
- Prefer preview / draft / simulation mode before destructive changes.
- If information is missing, ask only for the minimum needed to proceed.
- Never fabricate metrics, legal certainty, receipts, credentials, or evidence.
- Keep assumptions explicit.
## Suggested prompts
- 文献矩阵
- build a literature matrix
- 整理论文综述
## Use of script and resources
Use the bundled script when it helps the user produce a structured file, manifest, CSV, or first-pass draft.
Use the resource file as the default schema, checklist, or preset when the user does not provide one.
## Boundaries
- This skill supports planning, structuring, and first-pass artifacts.
- It should not claim that files were modified, messages were sent, or legal/financial decisions were finalized unless the user actually performed those actions.
## Compatibility notes
- Directory-based AgentSkills/OpenClaw skill.
- Runtime dependency declared through `metadata.openclaw.requires`.
- Helper script is local and auditable: `scripts/build_matrix.py`.
- Bundled resource is local and referenced by the instructions: `resources/matrix_schema.csv`.Related Skills
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