Research workflow design
Create a data contract before collecting product, keyword, review, or creator evidence.
Agents01 02 03
Failed or incomplete first runs are refundedEcommerce Research Quality Check
Make ecommerce research reproducible, comparable, and auditable
Define a data contract, preserve raw evidence and transformations, and separate facts, calculations, inferences, and recommendations.
What the Agent prepares
- A reproducible research and data contract
- An evidence, transformation, calculation, and version ledger
- Comparability gaps, missing fields, errors, and unresolved unknowns
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A tool result is not yet reliable decision evidence
Share the research question, decision use, marketplace, country, time window, tools, requests, raw-result references, cleaning rules, formulas, and current conclusion. The Agent traces the evidence chain from input to recommendation.
The result defines entities, fields, units, filters, deduplication, missing values, transformations, and error records. Facts, calculations, inferences, unknowns, and recommendations stay separate, and the Agent does not invent missing tool output.
Use it for
Conflicting-report audit
Find differences in marketplace, time, filters, fields, units, deduplication, or formulas.
Decision evidence pack
Prepare a traceable record that another analyst can review or rerun.
Example task
Audit this Amazon product research workflow before we trust the result
What the Agent prepares
- A reproducible research and data contract
- An evidence, transformation, calculation, and version ledger
- Comparability gaps, missing fields, errors, and unresolved unknowns
- A separated fact, calculation, inference, and recommendation report
How it works
Fix the research contract
Define the decision, entities, marketplace, time, fields, units, filters, and stop condition.
Trace evidence and changes
Record tool requests, raw results, errors, cleaning, deduplication, formulas, and versions.
Separate conclusion layers
Keep observed facts, calculations, inferences, unknowns, and recommendations independently reviewable.
Auditability without fabricated tool access
- The Agent does not claim to run a tool, access live data, or verify a raw result unless that capability and evidence are actually available.
- It does not invent missing requests, outputs, fields, timestamps, formulas, errors, or research evidence.
- Users remain responsible for data permissions, platform rules, interpretation, and the final business decision.
Frequently asked questions
Why can two tools produce opposite answers?
They may use different entities, marketplaces, time windows, filters, missing-value rules, deduplication, units, or calculations.
Does the Agent connect to research tools?
Not by default. Provide exported data and run records. Missing access or evidence remains unknown and is not invented.
What makes a study reproducible?
Another reviewer can reconstruct the question, inputs, requests, raw evidence, transformations, calculations, versions, and decision rules.
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