research assistant skill
Structured research assistant providing quick briefs, deep dives, and side-by-side decision comparisons.
$5
Works with the AI tools you already use
Claude Code
Cursor
Codex CLI
Muse
Dots+22 moreClaude CodeCursorCodex CLIMuseDots
OpenClaw
Manus
Grok
Grok Bot+18 agentsresearch assistant skill
Example session with this skill installed
I need to decide between using PostgreSQL, MongoDB, and DynamoDB for a new high-traffic messaging app. I care about scaling, cost, and developer experience. Give me a comparison.
- Read your context and instructions
- Compiled the research assistant
- Generated the document
I'll help you research that. I've analyzed these database options based on your requirements for a high-traffic messaging system, focusing on horizontal scalability and operational overhead.
DECISION BRIEF: Messaging App Database Selection
OPTIONS COMPARED
| Factor | PostgreSQL | MongoDB | DynamoDB |
|---|---|---|---|
| Data Model | Relational / JSONB | Document (BSON) | Key-Value / Document |
| Scaling | Vertical (Primary) + Read Replicas; Citus for Sharding | Native Sharding / Replica Sets | Seamless Auto-scaling (Serverless) |
| Consistency | Strong ACID compliance | Tunable (Strong/Eventual) | Eventual (default) or Strong |
| Dev Experience | High; standard SQL, mature ORMs | High; flexible schema, JSON-like | Moderate; proprietary API, strict indexing |
| Price/Cost | Managed (RDS/Cloud) hourly rate | Tiered (Atlas) or self-hosted | Pay-per-request (can spike with scans) |
| Pros | Rock-solid reliability; complex joins | Schema flexibility; easy horizontal scaling | Zero maintenance; massive throughput |
| Cons | Sharding is complex to manage | Memory intensive; high storage overhead | No joins; vendor lock-in; rigid schema |
RECOMMENDATION
For a messaging app where horizontal scale is critical but data structure is relatively predictable (messages, threads, users),
MongoDB is the strongest fit. It handles the high-write volume of messaging better than standard Postgres while offering more flexibility for message metadata than DynamoDB's rigid indexing.
THINGS TO VERIFY BEFORE DECIDING
- Hosting Costs: Compare Amazon RDS (Postgres) vs MongoDB Atlas pricing for 1TB of data.
Latency Requirements: Benchmark DynamoDB global tables if your messaging app requires sub-30ms cross-region latency.
3. Team Expertise: Assess if your team is comfortable managing sharded clusters or prefers a serverless approach.
Next steps
- Would you like me to do a Deep Dive into MongoDB sharding strategies for messaging?
- Should I add a fourth option like Apache Cassandra/ScyllaDB to this comparison?
- Do you want a Quick Brief on the specific costs of managed Postgres vs MongoDB Atlas?
research-assistant-skill.pdf
PDF · document
Example file from a real run - the skill writes it into your workspace.
Connects securely to your tools. The creator never sees your data.
What you get
About this skill
The problem
Standard LLM responses often fluctuate between surface-level summaries and unorganized "walls of text." Users struggle to get specific, actionable facts or side-by-side comparisons without manual prompting for structure and clarity.
What it does
- Conducts a structured consultation to identify your specific research goals, constraints, and existing knowledge.
- Delivers research in three distinct modes: Quick Brief (scannable facts), Deep Dive (comprehensive analysis), or Decision Research (tabular comparison).
- Replaces vague "topic labels" with concrete claims, specific data points, and actionable findings.
- Provides "Source Roadmaps" with specific search terms and resource types to verify data offline.
- Explicitly identifies knowledge gaps and items that require manual verification to ensure accuracy.
Why this beats prompting it yourself
This skill enforces a rigorous consultation phase that extracts the "why" behind your research, ensuring the output aligns with your end goal. It automates the formatting of complex tables and deep-dive structures that usually require multiple follow-up prompts to achieve. By prioritizing actual claims over generic descriptions, it saves you from filtering through AI fluff.
Use cases
- Comparing 3-4 SaaS tools or hardware options to make a purchasing decision.
- Getting a high-level technical briefing before a stakeholder meeting.
- Investigating a new market or niche to identify common pitfalls and key players.
- Creating a source-guided research roadmap for a deep-dive technical article.
Known limitations
Cannot browse the live web or access real-time pricing. Does not provide professional legal, medical, or financial advice.
How to install
Works the same in every agent - Claude, Cursor, Codex, Copilot and 20+ more.
- 1
Download the ZIP
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- 2
Unzip into your skills folder
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- 3
Ask your agent to use it
Restart the agent if it was already running. It picks the skill up automatically - no config needed.
Skills folder by agent
Click the path to copy it. Create the folder if it does not exist yet.
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