research-lookup
Look up current research information using the Parallel Chat API (primary) or Perplexity sonar-pro-search (academic paper searches).
Skill by beita6969
Chalk Labs
Need help deploying research-lookup?
Chalk Labs sets up agents like this inside real teams: connected to your tools, tested on your data, with a human in the loop where it matters.
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/beita6969-research-lookup
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
Get the weekly diff
The weekly diff: one email a week with new agent tools, notable updates and grade changes, plus security alerts for tools you follow. Double opt-in, one-click unsubscribe.
About
Use cases: backend, data, research
Reviews
Write a reviewNo reviews yet. Installed it? Reviews come from verified installers only. How reviews work
Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
- Runs as
- Python package
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/research-lookup
Tools it pre-approves 4
From allowed-tools in SKILL.md: the agent may use these without asking you each time.
ReadWriteEditBash
What's inside
- Skill name
research-lookup- Description
- Look up current research information using the Parallel Chat API (primary) or Perplexity sonar-pro-search (academic paper searches). Automatically routes queries to the best backend. Use for finding papers, gathering research data, and verifying scientific information.
- License
- MIT
- Compatibility
- PARALLEL_API_KEY and OPENROUTER_API_KEY required
- Allowed tools
- Read, Write, Edit, Bash
- Metadata
- skill-author: K-Dense Inc.
- Instructions
- 405 lines in SKILL.md · view on GitHub
Before installing
- Ships executable scripts
- Pre-approves any shell command
Files (6)
- README.md
- SKILL.md
- examples.py
- lookup.py
- research_lookup.py
- research_lookup.py · scripts/
SKILL.md (first lines)
# Research Information Lookup
## Overview
This skill provides real-time research information lookup with **intelligent backend routing**:
- **Parallel Chat API** (`core` model): Default backend for all general research queries. Provides comprehensive, multi-source research reports with inline citations via the OpenAI-compatible Chat API at `https://api.parallel.ai`.
- **Perplexity sonar-pro-search** (via OpenRouter): Used only for academic-specific paper searches where scholarly database access is critical.
The skill automatically detects query type and routes to the optimal backend.
## When to Use This Skill
Use this skill when you need:
- **Current Research Information**: Latest studies, papers, and findings
- **Literature Verification**: Check facts, statistics, or claims against current research
- **Background Research**: Gather context and supporting evidence for scientific writing
- **Citation Sources**: Find relevant papers and studies to cite
- **Technical Documentation**: Look up specifications, protocols, or methodologies
- **Market/Industry Data**: Current statistics, trends, competitive intelligence
- **Recent Developments**: Emerging trends, breakthroughs, announcements
## Visual Enhancement with Scientific Schematics
**When creating documents with this skill, always consider adding scientific diagrams and schematics to enhance visual communication.**
If your document does not already contain schematics or diagrams:
- Use the **scientific-schematics** skill to generate AI-powered publication-quality diagrams
- Simply describe your desired diagram in natural language
```bash
python scripts/generate_schematic.py "your diagram description" -o figures/output.png
```
---
## Automatic Backend Selection
The skill automatically routes queries to the best backend based on content:
### Routing Logic
```
Query arrives
|
+-- Contains academic keywords? (papers, DOI, journal, peer-reviewed, etc.)
| YES --> Perplexity sonar-pro-search (academic search mode)
|
+-- Everything else (general research, market data, technical info, analysis)
--> Parallel Chat API (core model)
```
### Academic Keywords (Routes to Perplexity)
Queries containing these terms are routed to Perplexity for academic-focused search:
- Paper finding: `find papers`, `find articles`, `research papers on`, `published studies`
- Citations: `cite`, `citation`, `doi`, `pubmed`, `pmid`
- Academic sources: `peer-reviewed`, `journal article`, `scholarly`, `arxiv`, `preprint`
- Review types: `systematic review`, `meta-analysis`, `literature search`
- Paper quality: `foundational papers`, `seminal papers`, `landmark papers`, `highly cited`
### Everything Else (Routes to Parallel)
All other queries go to the Parallel Chat API (core model), including:
- General research questions
- Market and industry analysis
- Technical information and documentation
- Current events and recent developments
- Comparative analysis
- Statistical data retrieval
- Complex analytical queries
### Manual Override
You can force a specific backend:
```bash
# Force Parallel Deep Research
python research_lookup.py "your query" --force-backend parallel
# Force Perplexity academic search
python research_lookup.py "your query" --force-backend perplexity
```
---
## Core Capabilities
### 1. General Research Queries (Parallel Chat API)
**Default backend.** Provides comprehensive, multi-source research with citations via the Chat API (`core` model).
```
Query Examples:
- "Recent advances in CRISPR gene editing 2025"
- "Compare mRNA vaccines vs traditional vaccines for cancer treatment"
- "AI adoption in healthcare industry statistics"
- "Global renewable energy market trends and projections"
- "Explain the mechanism underlying gut microbiome and depression"
```
**Response includes:**
- Comprehensive research report in markdown
- Inline citations from authoritative web sources
- Structured sections with key findings
- Multiple perspectives and data points
- Source URLs for verification
### 2. Academic Paper Search (Perplexity sonar-pro-search)
**Used for academic-specific queries.** Prioritizes scholarly databases and peer-reviewed sources.
```
Query Examples:
- "Find papers on transformer attention mechanisms in NeurIPS 2024"
- "Foundational papers on quantum error correction"From beita6969/ScienceClaw, MIT.
More from beita6969/ScienceClaw
- 0.608score
scienceclaw-benchmark-for51
beita6969
Use when a task asks to predict a phonon property of inorganic crystals from their structure, for example the frequency of the last peak of the phonon density…
SkillAFreshness: A★ 1KClaude Code +9 - 0.608score
scienceclaw-benchmark-for44
beita6969
Use when a task gives a covariate table plus, for each of many simulated observational datasets, a binary treatment vector and an outcome vector, and asks for…
SkillAFreshness: A★ 1KClaude Code +9 - 0.608score
scienceclaw-benchmark-for43
beita6969
Use when a task gives noisy OCR text of historical newspapers, periodicals or books (several languages, with metadata and a set of labelled OCR/ground-truth…
SkillAFreshness: A★ 1KClaude Code +9 - 0.608score
scienceclaw-benchmark-for34
beita6969
Use when predicting a binary molecular property such as HIV replication inhibition (OGB ogbg-molhiv, MoleculeNet-style activity) from SMILES strings and…
SkillAFreshness: A★ 1KClaude Code +9 - 0.608score
scienceclaw-benchmark-for42
beita6969
Use when a task gives hourly ICU records (vitals, labs, demographics, one stay per patient) with sepsis labels and asks for causal hour-by-hour sepsis alarms…
SkillAFreshness: A★ 1KClaude Code +9 - 0.608score
scienceclaw-benchmark-for33
beita6969
Use when forecasting day-ahead hourly electricity load of individual buildings (residential and commercial smart-meter data, BuildingsBench-style) from the…
SkillAFreshness: A★ 1KClaude Code +9 - 0.608score
scienceclaw-benchmark-for32
beita6969
Use when segmenting the hippocampus into anterior and posterior parts in small 3-D T1-weighted brain MRI crops (Medical Segmentation Decathlon Task04) from a…
SkillAFreshness: A★ 1KClaude Code +9 - 0.608score
scienceclaw-benchmark-for35
beita6969
Use when forecasting monthly tourism, visitor or other seasonal business and service series (Monash Tourism Monthly, 24-month horizon, period 12) from each…
SkillAFreshness: A★ 1KClaude Code +9 - 0.608score
scienceclaw-benchmark
beita6969
Index of the 23 discipline skills (FoR30-FoR52) that mirror the disciplines of the companion ScienceClaw-Eval benchmark: find which discipline skill fits a…
SkillAFreshness: A★ 1KClaude Code +9 - 0.608score
scienceclaw-benchmark-for30
beita6969
Use when segmenting top-down field or UAV RGB images of crops (sugar beet, PhenoBench-style) into soil / crop / weed semantics plus crop-plant and crop-leaf…
SkillAFreshness: A★ 1KClaude Code +9 - 0.608score
scienceclaw-benchmark-for31
beita6969
Use when ranking or predicting the fitness effect of single amino-acid substitutions in a protein (deep mutational scanning, ProteinGym-style assays) from…
SkillAFreshness: A★ 1KClaude Code +9 - 0.608score
scienceclaw-benchmark-for46
beita6969
Use when a task gives Python programming problems (a function stub with docstring or a task description, an entry-point name, a few public assert tests) and…
SkillAFreshness: A★ 1KClaude Code +9
Signals
- Stars
- 1,019
- Forks
- 109
- Open issues
- 1
- Last commit (this folder)
- Mar 12, 2026 (7 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/beita6969/ScienceClaw
- Website
- scienceclaw.science
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
Same skill elsewhere
Copies of this SKILL.md published by others; search shows only one of them.
More from beita6969
- 0.608score
scienceclaw-benchmark-for33
beita6969
Use when forecasting day-ahead hourly electricity load of individual buildings (residential and commercial smart-meter data, BuildingsBench-style) from the…
SkillAFreshness: A★ 1KClaude Code +9 - 0.608score
scienceclaw-benchmark-for34
beita6969
Use when predicting a binary molecular property such as HIV replication inhibition (OGB ogbg-molhiv, MoleculeNet-style activity) from SMILES strings and…
SkillAFreshness: A★ 1KClaude Code +9 - 0.608score
scienceclaw-benchmark-for30
beita6969
Use when segmenting top-down field or UAV RGB images of crops (sugar beet, PhenoBench-style) into soil / crop / weed semantics plus crop-plant and crop-leaf…
SkillAFreshness: A★ 1KClaude Code +9 - 0.608score
scienceclaw-benchmark-for32
beita6969
Use when segmenting the hippocampus into anterior and posterior parts in small 3-D T1-weighted brain MRI crops (Medical Segmentation Decathlon Task04) from a…
SkillAFreshness: A★ 1KClaude Code +9 - 0.608score
scienceclaw-benchmark
beita6969
Index of the 23 discipline skills (FoR30-FoR52) that mirror the disciplines of the companion ScienceClaw-Eval benchmark: find which discipline skill fits a…
SkillAFreshness: A★ 1KClaude Code +9 - 0.608score
scienceclaw-benchmark-for35
beita6969
Use when forecasting monthly tourism, visitor or other seasonal business and service series (Monash Tourism Monthly, 24-month horizon, period 12) from each…
SkillAFreshness: A★ 1KClaude Code +9
Done for you
Rather not set it up yourself?
Chalk Labs scopes, builds and runs agents for your team: the task audit, the eval harness, the integrations and the weekly ops report. Fixed scope, priced before we start.
See how we build AI agents →Read the case studies
Chalk Labs is a two-founder AI and growth studio. We build AI agents, CRMs and MVPs for Web3 and AI companies, and have shipped 50+ product and token launches.
- launches shipped
- 50+
- launches shipped
- media placements
- 500+
- media placements
- founders on every account
- 2
- founders on every account
Press we've placed: Forbes · CoinDesk · Decrypt · Cointelegraph · The Block
Rahil Jain, Co-founder, Chalk Labs. Ex-Goldman Sachs engineer. You talk to the person who builds it.
Get research-lookup running in your business
Tell us what you want to automate. A founder replies within one working day with a plan, not a pitch deck.
Cite this page
research-lookup skill. Agent Mart. https://agentmart.dev/skills/beita6969-research-lookup (last updated 2026-10-24)