related-work-survey
>
pinned to #68098d5updated 2 weeks ago
Ask your AI client: “install skills/related-work-survey”.
Requires the metahub MCP server installed in your client. Set up MCP.
mh install skills/related-work-surveymetahub onboarded this repo on the author's behalf.
If you own github.com/jxtse/scientific-research-skills on GitHub, claim the listing to take over publishing. Your claim preserves the existing eval history and badges; only the curator label is replaced with verified-publisher on your next publish.
Stars
54
Last commit
2 weeks ago
Latest release
published
- #academic-research
- #agent-skill
- #claude-skill
- #literature-review
- #zotero
About this skill
Pulled from SKILL.md at publish time.
Systematic literature survey for positioning a research contribution.
Evaluation report
WarningsAutomated checks the publisher passed at publish time — structure, docs, safety, and whether the artifact behaves as claimed.68098d5· 2 weeks ago
Documentation
41Description qualitywarn
21 words · 101 chars — manifest description is empty; graded the GitHub repo description instead
A skill's manifest description doubles as its trigger — add one to SKILL.md (15+ words, e.g. “use this skill when …”).
README is present and substantial
13,987 chars · 7 sections · 5 code blocks
Tags / topics declared
5 total — academic-research, agent-skill, claude-skill, literature-review, zotero
README has usage / example sections
found: Quick Start · Installation · Example
Homepage / docs URL declared
no homepage declared (registry will use the repo URL) — info-only, not blocking
Release history
1- releasecurrent68098d5warn2 weeks ago
Contents
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
Reviews
No reviews yet. Be the first.
Related
Frontend Slides
Create beautiful slides on the web using Claude's frontend skills
Verification Before Completion
Evidence before assertions, always
Writing Plans
Turn specs into phased implementation plans
mh install skills/related-work-survey