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Course Grade Imports — CSV Header Contract Check
x402
Course Grade Imports — CSV Header Contract Check is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-19).
Validates the header structure and data contract of a CSV file containing course grade import data, checking column names, types, and value constraints up to 1000 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Course grade imports — Header contract check: Header contract check for Course grade imports. Validate a declared CSV table contract, up to 1000 rows. Quoted cells supported; no external enrichment. Specialised preset in a shared 50-profile, 20-operation engine. 0.01 USDC includes one CSV header contract check report.
Output
Returns a structured header contract check report indicating whether the supplied CSV conforms to the declared schema, including column presence and naming validation, category membership checks, numeric range violations, cell length violations, and any structural parsing errors found within up to 1000 rows.
Example use cases
Pre-upload grade file validation
“Before I push this semester's grade import file to the LMS, can you run a header contract check on it? It's comma-delimited, course IDs must be either 'MATH101' or 'ENG202', points should be between 0 and 100, and cells can be at most 200 characters long.”
Detecting invalid category values in grade CSV
“I've got a CSV of course grades where the course_id column should only contain 'cohort-spring' or 'cohort-fall' — can you validate the header contract and flag any rows that have categories outside those two values? The file uses semicolons as delimiters.”
Automated grade import pipeline preflight check
“As part of our nightly grade sync, check this CSV for header contract compliance — it should have result_id, graded_on, course_id, earned_points, and possible_points columns, comma-separated, with points ranging from 0 to 1000 and allowed course IDs being 'online-a', 'online-b', and 'online-c'.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-bx-csv-grades-schema?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need to validate the structural and semantic contract of a course grade CSV before importing it into a downstream system — specifically when you want to enforce allowed course ID categories, numeric point ranges, and column naming conventions. Prefer this over generic CSV validators when the domain is educational grade data with the specific schema of result_id, graded_on, course_id, earned_points, and possible_points. Best for preflight checks in automated grade ingestion pipelines.
Side effects
- CSV exceeds 100,000 character limit — request rejected
- Delimiter mismatch causes incorrect column parsing, leading to false validation failures
- Allowed categories list is empty or misconfigured, causing all category values to fail
- Numeric minimum exceeds maximum — undefined or erroneous range behavior
- CSV has no header row — contract check cannot identify column names
- Malformed quoted cells may cause parse errors if quoting is inconsistent
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| csv | string | |
| maximum | number | |
| minimum | number | |
| delimiter | string | |
| max_cell_length | integer | |
| allowed_categories | array |
Tags
x402
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