Define what to check
Whether material is complete, fields consistent, citations correct, output in the right place — checks track business needs.
XUNYE Technology · RELIABILITY & EVALUATION
Reliability & Evaluation
Check quality on real tasks, so every change can be verified.
XUNYE brings task results, execution records, and human judgment into verification. Around project needs we define check items, record discovered problems, and re-verify key flows after system changes.
How it runs
From one failure, the next check.
First keep inputs and run evidence, and locate whether the problem is in material, generation, tools, or flow — then write the expected behavior into a reproducible check. Verification looks at both the final result and whether key steps ran as required.
01
Task sample
Input · expected result · conditions
02
Run record
Material · steps · actual output
03
Locate the problem
Facts · fields · flow · judgment
04
Fix & re-verify
Rerun the case · check linked flows
Evidence of failure → explicit expectation → fix → re-verify on the same task
In practice
Verification follows the delivery.
Different tasks are checked by different standards.
Keep reviewable records
Inputs, key steps, and results are logged so problems trace to a concrete step.
Turn problems into checks
For each error, keep the reproduction condition and expected behavior for future fixes and updates.
Split function from judgment
Format, fields, and flows follow explicit rules; professional conclusions and content quality are reviewed by owners.
A sample handoff
Turn 'looks fine' into a definite verdict.
A verification record for a concrete task.
- Task
- Collect order records for one live show
- Completeness
- All required records present; no gaps or duplicates
- Consistency
- Order fields match their sources
- Calculation
- Totals map to line items one by one
- On failure
- Locate the record; never mask gaps with zeros
- Re-verify
- Fix, then check linked summaries and outputs
Verification & boundaries
Checks have scope; results have basis.
01
Key task pass rate
02
Known issues not recurring
03
Delivery completeness
04
Human review conclusions
No single number for quality
Format, facts, task completion, and business effect are judged separately; reports state test material and conditions.
Business judgment is human
Machines check fields, format, rules; content quality and professional conclusions are reviewed by owners with reasons kept.
Re-verify after change
Model, prompt, material, or interface changes re-run affected key tasks. Project checks are not a general evaluation platform.
FAQ
Mechanisms, conditions, and boundaries.
01How do real errors become repeatable checks?
Save the input, versions, wrong output, and expected result; shrink it to a reproducible condition. After a fix, rerun the original case, then check affected steps in the same flow.
02Can AI grade its own output?
It can pre-screen, not replace independent checking. Fields and calculations follow explicit rules; subjective quality is set by business owners, sometimes comparing multiple outputs. A self-pass is not acceptance.
03Is a successful demo the same as acceptance?
A demo shows the process runs. Acceptance checks key tasks on agreed material, permissions, and environment — including failure, gaps, and recovery — with records kept.
04Is there a unified evaluation platform today?
We define check items per project and keep issue and regression records. A formal benchmark suite, automatic grader, or continuous platform is a scoping decision — current engineering checks are not a full platform.
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