How Do SciSpace Credits Work?
TL;DR
1-min readSciSpace credits are tied to the work performed, so efficient use begins before you click Run. Check your current plan, distinguish a quick tool action from a multi-step Agent task, prepare the files and output requirements, and pilot a smaller scope. Clear prompts and early validation reduce repeated runs and wasted credits.
How to do it
Review the current plan and usage information shown in your SciSpace account.
Check the plan and current usage information in the account before starting. Record the available credits and any plan-specific limits that affect the intended task.
Estimate whether the task is a quick tool action or a multi-step research workflow.
Classify the task as a focused tool action or a multi-step Agent workflow and estimate the number of files, searches, analyses, and outputs involved. Reduce unnecessary scope before launch.
Prepare files, criteria, and desired outputs before starting.
Prepare files, criteria, terminology, and the desired output format so the system does not repeat work to clarify the request. Reuse a tested prompt when the task is recurring.
Pilot a smaller scope, inspect the result, and scale only after the workflow is correct.
Run a small pilot, inspect quality and usage, then scale only after the workflow is correct. If usage is higher than expected, shorten the source set or split the task into reviewable stages.
Watch the tutorial3 min
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Frequently asked questions
What does this tutorial cover?
SciSpace credits are tied to the work performed, so efficient use begins before you click Run. Check your current plan, distinguish a quick tool action from a multi-step Agent task, prepare the files and output requirements, and pilot a smaller scope. Clear prompts and early validation reduce repeated runs and wasted credits.
What should I do first?
Check the plan and current usage information in the account before starting. Record the available credits and any plan-specific limits that affect the intended task.
What is the final step?
Run a small pilot, inspect quality and usage, then scale only after the workflow is correct. If usage is higher than expected, shorten the source set or split the task into reviewable stages.
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