related-work-survey

name

related-work-survey

description

Conducts a systematic related-work / literature-survey / state-of-the-art review for a research question by defining survey dimensions, searching each axis, building a taxonomy of prior work, identifying the gap, and producing a positioning narrative for a paper's Related Work section. Goes beyond a flat paper list to deliver structured analysis. Use when the user is starting a new research project and needs to map the landscape, asks "what's been done on X?" or "how does my idea compare to existing work?", needs to write or revise a Related Work / Background / Prior Art section, wants to identify a research gap or position their contribution, or asks to build a taxonomy of approaches in a research area.

Related Work Survey

Systematic literature survey for positioning a research contribution.

When to Use

• User starts a new research project and needs landscape understanding
• User asks "what's been done on X?"
• User needs to write a related work section
• User wants to identify the gap their work fills

Workflow

Step 1: Define the Research Question

Work with the user to pin down:

• Core question: What specific problem are we solving?
• Key concepts: What are the 3-5 key terms/concepts?
• Scope boundaries: What's in scope vs. adjacent but out of scope?

Step 2: Identify Survey Dimensions

Every research topic sits at an intersection of multiple dimensions. Identify 2-4 axes:

Example for "Neural-Symbolic Decomposition in LLM Agents":

• Axis 1: Neuro-symbolic integration approaches
• Axis 2: LLM agent architectures (harness, scaffolding)
• Axis 3: Adaptive/metacognitive planning
• Axis 4: Text analysis at scale (specific application)

Step 3: Search Each Dimension

For each axis, use literature-search skill with targeted queries:

Axis 1 → "neuro-symbolic integration LLM reasoning 2024 2025"
Axis 2 → "LLM agent harness scaffolding architecture survey"
Axis 3 → "metacognitive planning adaptive tool use LLM"
Axis 4 → "large scale text analysis LLM code generation quality"

Collect 10-20 papers per axis, then deduplicate across axes.

Step 4: Build the Taxonomy

Organize papers into a structured taxonomy:

## Related Work Taxonomy

### 1. Neuro-Symbolic Integration
  1.1 Neural reasoning with symbolic verification
  1.2 Symbolic planning with neural execution
  1.3 Adaptive decomposition (our focus)

### 2. LLM Agent Architecture
  2.1 Harness engineering
  2.2 Self-evolving agents
  2.3 Meta-Harness optimization

### 3. ...

Step 5: Identify the Gap

The gap is where your work lives — the intersection that no existing paper covers:

Paper A does X but not Y.
Paper B does Y but not X.
We do both X and Y, connected by Z.

Step 6: Write the Narrative

Structure the related work section as a story:

1. Context: What's the broader field?
2. Prior art per axis: What has been done?
3. Gap statement: What's missing?
4. Our position: How do we fit in?

Output Format

Deliver a structured document:

# Related Work Survey: [Topic]

## Research Question
[1-2 sentences]

## Taxonomy
[Structured tree]

## Key Papers
| Paper | Axis | Key Contribution | Gap Relative to Us |
|-------|------|------------------|--------------------|
| ...   | ...  | ...              | ...                |

## Identified Gap
[Clear statement of what no existing work covers]

## Recommended Positioning
[How to frame our contribution relative to existing work]

Principles

• Be honest about overlap: If someone has done something very similar, acknowledge it
• Recent > old: Prioritize 2024-2026 papers for positioning; cite older seminal works for foundations
• Quality > quantity: 20 well-chosen papers > 50 tangentially related ones
• Track the conversation: Note who cites whom — citation chains reveal intellectual lineage
• Check workshops/findings: Important early-stage work often appears in workshop papers