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vibe-research skill

/skills/ivangdavila/vibe-research

This skill conducts autonomous literature review, hypothesis generation, analysis, and synthesis under human guidance to accelerate rigorous research.

npx playbooks add skill openclaw/skills --skill vibe-research

Review the files below or copy the command above to add this skill to your agents.

Files (4)
SKILL.md
2.6 KB
---
name: Vibe Research
slug: vibe-research
version: 1.0.0
description: Conduct AI-led research with autonomous literature review, hypothesis generation, analysis, and synthesis while human provides vision.
metadata: {"clawdbot":{"emoji":"🔬","requires":{"bins":[]},"os":["linux","darwin","win32"]}}
---

## When to Use

User has a research question or knowledge gap. Agent takes ownership of the full research cycle: scanning literature, generating hypotheses, running analyses, synthesizing findings. Human provides direction and oversight, AI executes.

## Quick Reference

| Topic | File |
|-------|------|
| Research pipeline | `pipeline.md` |
| Risk mitigation | `risks.md` |

## Core Concept

**Traditional research:** Human-led, human-executed
**Deep research:** Human-led, AI-assisted  
**Vibe research:** Human-directed, AI-led

The human sets the question and validates outputs. The agent handles literature synthesis, hypothesis generation, data analysis, and write-up autonomously.

## Core Rules

### 1. Full-Cycle Ownership
Agent executes the complete pipeline:
1. **Gap identification** — What's unknown or contested?
2. **Literature synthesis** — Scan, summarize, cross-reference sources
3. **Hypothesis generation** — Propose testable claims
4. **Analysis design** — Define methodology
5. **Execution** — Run analyses, gather data
6. **Synthesis** — Write findings with citations

### 2. Vision from Human, Execution from Agent
- Human provides: research question, domain constraints, success criteria
- Agent handles: reading papers, connecting ideas, running experiments, drafting
- Human validates: key decisions, final outputs, methodology choices

### 3. Transparent Reasoning
- Cite every claim: source, page, quote
- Show reasoning chain for hypotheses
- Log all analytical steps for reproducibility
- Flag confidence levels (high/medium/low)

### 4. Proactive Gap Detection
Don't wait for instructions. When analyzing a topic:
- Identify contradictions in literature
- Spot under-explored areas
- Suggest follow-up experiments if results are ambiguous
- Pull additional sources when context is insufficient

### 5. Hallucination Prevention
- Only claim what sources support
- Distinguish: "Source X says..." vs "I infer..."
- When uncertain, say so explicitly
- Cross-verify critical facts across multiple sources

## Vibe Research Traps

- Treating AI output as ground truth → always require human validation of key findings
- Skipping methodology transparency → document every step for reproducibility
- Overwhelming human with raw output → synthesize into actionable insights
- Losing the human's analytical skills → keep them engaged in critical thinking

Overview

This skill conducts end-to-end, AI-led research while you provide the guiding vision and validation. It autonomously scans literature, generates hypotheses, designs and runs analyses, and synthesizes reproducible findings. The agent emphasizes transparent reasoning, citation-backed claims, and proactive identification of gaps.

How this skill works

You give a research question, domain constraints, and success criteria. The agent autonomously identifies knowledge gaps, performs literature synthesis, proposes testable hypotheses, designs methodologies, executes analyses, and drafts results with source-level citations and confidence labels. It logs every analytical step for reproducibility and flags items that need your validation.

When to use it

  • You have a clear research question but limited time to perform full literature review and experiments.
  • You need a reproducible synthesis of a contested or fragmented literature.
  • You want hypothesis generation and prioritization before committing resources to experiments.
  • You require end-to-end support from search and analysis through write-up while retaining final decision authority.
  • You need proactive discovery of contradictions or under-explored areas in a field.

Best practices

  • Provide a precise research question, domain boundaries, and success metrics up front.
  • Set checkpoints for human validation on methodology, critical assumptions, and final claims.
  • Require source-level citations and cross-verification for any factual assertions.
  • Ask for concise executive summaries plus detailed reproducibility logs to avoid information overload.
  • Use the agent’s proactive suggestions for follow-up experiments as prompts, not final decisions.

Example use cases

  • Performing an autonomous literature review and meta-analysis on a clinical or technical question.
  • Generating and prioritizing testable hypotheses for a new product feature based on academic and industry sources.
  • Running exploratory analyses on pooled open datasets and delivering reproducible code and results.
  • Synthesizing conflicting studies into a clear summary with recommended next-step experiments or data collection.
  • Archiving a research trail with citations, analytic logs, and a draft manuscript for rapid peer review.

FAQ

How much control do I retain over the research?

You retain vision and final validation. The agent executes the pipeline but requires sign-off at predefined checkpoints for methods and final outputs.

How does the agent prevent hallucinations?

The agent cites every claim to specific sources, distinguishes inference from quotation, cross-verifies critical facts across multiple sources, and flags low-confidence items for human review.