Article summary
A complete QA workflow for Telegram full-format exports covering TXT lineage, Excel schemas, field-level coverage, exceptions, and controlled handoff.
Validating a Telegram full-format export is a data-lineage exercise. A reviewer should be able to start with any Excel row, identify the task and execution time, return to the normalized TXT number, and distinguish account fields from avatar-analysis outputs. A file that merely contains many populated columns has not yet passed acceptance.
Control the batch before examining its contents
Create a control sheet with source filename, source owner, original rows, normalized rows, unique numbers, invalid rows, task ID, execution time, export rows, and reviewer. Keep a source_row_id-to-phone map so deduplicating the TXT input does not disconnect results from authorized business records.
| Control test | Pass condition | Failure action |
|---|---|---|
| Input lineage | Every submitted number maps to a source row | Stop handoff and rebuild the map |
| Row reconciliation | Count differences are explained | Create an exception list |
| Task metadata | ID, date, and schema are recorded | Recover metadata before merging |
Validate the exact full-format schema
The current field definition can include phone number, TG UserID, TG username, offline time, active days, First Name, Last Name, TG VIP, frozen status, avatar URL, age, gender, skin color, avatar type, and avatar people count. Verify actual export headers against the task definition on the Telegram product page. Do not add columns copied from another service.
Apply field-type and relationship tests
- Phone numbers remain text and retain country codes.
- TG UserID and TG username are separate columns.
- Offline time and active days use documented types.
- Avatar URL is distinct from all image-analysis outputs.
- Age, gender, skin color, avatar type, and people count accept blank values.
- Internal review labels never overwrite raw task fields.
Measure completeness as a profile, not one score
Calculate separate coverage for account identifier, username, names, status, avatar URL, and image-analysis fields. One overall percentage hides whether the gap is a missing account row, an optional profile field, or an unsuitable image. Compare rates only across runs with the same schema and documented input rules.
Interpretation guidance for this field family is collected in the Telegram full-format hub.
Classify exceptions before deciding on a rerun
| Exception class | Example | Next step |
|---|---|---|
| Input | Invalid or incomplete international number | Correct only from an authoritative source |
| Task | Whole row absent or failed | Review task status and retry separately if justified |
| Profile | Username or name blank | Preserve the blank |
| Avatar | No URL or inaccessible image | Record the image state |
| Analysis | Some visual fields missing | Mark analysis unavailable; do not infer |
Use sampling to test the rules
Sample normal rows and every exception class. Reconcile the phone with the TXT input, compare raw and working tables, and confirm that no transformation silently filled blanks. Sampling should validate process behavior, not search the web for extra personal data. Broader Telegram task boundaries appear in the Telegram research hub.
Deliver an evidence package, not a loose spreadsheet
- Untouched Excel export.
- Governed working table with source_row_id, task_id, checked_at, and review_status.
- Field dictionary defining source, type, and blank treatment.
- Acceptance note with counts, coverage, exceptions, samples, and open issues.
The upload artifact is TXT with one normalized number per line; Excel is the output and review format. Keep both under appropriate access controls and retention rules.
Frequently asked questions
Should every full-format field be populated?
No. The schema lists fields the task can return. Optional profile data, absent avatars, and unsuitable images can produce legitimate blanks.
Can blank analysis values be replaced by defaults?
Not in the raw columns. A display layer may use “not returned” if its rule is documented and remains separate from actual values.
How should repeated numbers be handled?
Submit a unique normalized TXT list but retain a mapping to every authorized source row. Re-expand only after the result is validated.
When should the task be rerun?
Rerun documented task failures or cases requiring a newer observation. Do not repeatedly submit successful rows merely to eliminate legitimate blanks.
Acceptance succeeds when the result remains explainable
A trustworthy full-format delivery preserves lineage, schema, time, missingness, and exceptions. Those controls matter more than the raw number of populated cells because they let another reviewer reproduce every decision.
