Related Work Survey
SkillDev toolsConducts 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.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Related Work Survey skill
What this skill tells your AI
The instructions your AI receives, as published by jxtse/scientific-research-skills in skills/related-work-survey/SKILL.md and read by ahel’s review.
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:
- Context: What's the broader field?
- Prior art per axis: What has been done?
- Gap statement: What's missing?
- 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
Signals
- GitHub stars
- 68
- Forks
- 7
- Last commit
- May 2026
Advanced
- Catalog kind
- skill
- Gateway key
related-work-survey- Source
- github.com/jxtse/scientific-research-skills