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SciSpace Agent Prompting Tutorial: Write Better Research Prompts

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TL;DR

1-min read

This tutorial focuses on writing strong prompts for SciSpace Agent, since the quality of the output depends heavily on how you ask. It is aimed at people who already use the agent and want more precise results with fewer credits and less trial and error, and it works through concrete examples rather than general tips.

Key takeaways

  • Vague prompts tend to use up credits and return broad, generic answers, while well-built prompts lead to precise, structured output backed by citations.
  • A strong prompt states the research topic precisely, the task to be done, the scope such as years, study types or disciplines, and the output format, for example a table with specific columns.
  • Side-by-side comparisons of weak and strong prompts show how differences in wording change both the output and the number of credits consumed.
  • Live demonstrations show how to refine and iterate a prompt until the result is accurate and efficient, tightening whichever part missed the mark.
  • To save credits, define scope and expected output up front, break large jobs into well-defined steps and refine an existing result instead of starting over.
  • One detailed prompt suits a well-defined task, while a sequence of focused prompts works better for exploratory or multi-stage work where you check each step.
Apply it

To apply this, rewrite your next SciSpace Agent request with an explicit topic, task, scope and output format, then refine the result rather than starting again.

How to do it

  1. Avoid vague prompts

    Recognise that vague prompts waste credits and return broad, unfocused answers. Start every request with a specific goal in mind.

  2. Build prompts for your use case

    Write SciSpace Agent prompts tailored to your own research use case. Specific prompts lead to precise, structured output backed by citations.

  3. Compare weak and strong prompts

    Run a weak prompt and a strong prompt side by side and compare their outputs. Seeing the difference shows what details matter.

  4. Watch your credit usage

    Compare how many credits each prompt consumes. Better prompt quality reduces trial and error and saves credits.

  5. Refine and iterate prompts

    Refine your prompt guided based on the results you get. Iterating deliberately leads to accurate, efficient results.

Watch the tutorial45 min

SciSpace Agent Prompting Tutorial: Write Better Research PromptsPlay video: SciSpace Agent Prompting Tutorial: Write Better Research Prompts

Chapters

  1. Welcome and speaker introduction
  2. SciSpace Agent vs ChatGPT: what is different for research?
  3. What can SciSpace Agent do that other SciSpace tools can't?
  4. Why prompting SciSpace Agent right the first time saves credits
  5. Vague prompt example: search papers and write a report
  6. How to write a detailed prompt for a 5-page LaTeX research report
  7. Why vague prompts make the AI agent assume things and waste credits
  8. Can AI turn a research paper PDF into a live website?
  9. How many credits does SciSpace Agent use? Simple vs complex prompts
  10. How to get SciSpace Agent to write your research prompt
  11. How to write a good AI research prompt: context, task, constraints, output
  12. How to use the SciSpace Agent prompt builder (Build your task)
  13. How to find the right conference and submission deadlines with AI
  14. How to analyze multiple research PDFs at once and create a report
  15. Systematic literature review full text screening with SciSpace Agent
  16. PRISMA flow diagram generated by SciSpace Agent
  17. Key rule for prompting an AI research agent

Try this on SciSpace

Frequently asked questions

What makes a good prompt for an AI research agent?

A good prompt states the research topic precisely, the task you want done, the scope (such as years, study types or disciplines) and the format of the output, for example a table with specific columns. Adding context about your purpose helps the agent prioritise. Iterate by tightening whatever part of the result missed the mark.

How can I use fewer credits in SciSpace Agent?

Clear, specific prompts reduce the need for repeated attempts, which is where credits are often lost. Define the scope and expected output up front, break large jobs into well-defined steps, and refine an existing result rather than starting over. This tutorial compares credit usage between weak and strong prompts to show the difference.

Should I write one long prompt or several short ones?

Both can work. A single detailed prompt suits a well-defined task with a known output. For exploratory or multi-stage work, a sequence of focused prompts lets you check each step before moving on. In either case, be explicit about what you want and review the output before building on it.

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