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Course Grade Imports — Declared Column Projection
x402
Course Grade Imports — Declared Column Projection 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 a CSV table of course grade records against a declared column contract, reporting column projection compliance for up to 1000 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Course grade imports — Declared column projection: Declared column projection 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 declared column projection report.
Output
Returns a declared column projection report for the submitted course grade CSV, indicating whether the columns match the declared contract, any violations found, and compliance status across up to 1000 rows.
Example use cases
Pre-upload grade file column check
“Before I push this semester's grade records to the LMS, can you validate this CSV to make sure all the declared columns are present and correct? It's comma-delimited, categories should only be 'group-a' or 'group-b', and points should be between 0 and 1000.”
Automated grade import pipeline validation
“I'm running a nightly grade import job and need to verify that tonight's CSV file has the right column projection — comma delimiter, allowed categories are 'math-101' and 'eng-202', and no cell should be longer than 500 characters. Here's the CSV content.”
Catching bad columns in third-party grade export
“A third-party system exported this course grades CSV for me but I'm not sure the columns match our expected contract. Can you run a declared column projection check on it using semicolon as the delimiter, with allowed categories 'cohort-x' and 'cohort-y', and point values between 0 and 200?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-bx-csv-grades-projection?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need to validate that a course grade CSV file conforms to a declared column schema before ingesting it into a grade management system. It is purpose-built for the course grades domain with preset column expectations (result_id, graded_on, course_id, earned_points, possible_points) and supports category whitelisting and numeric range enforcement. Prefer it over generic CSV validators when your use case is specifically grade import pipelines.
Side effects
- CSV exceeds 100,000 character limit — request rejected
- More than 1000 rows in CSV — validation may be truncated or rejected
- Invalid delimiter specified — must be comma, semicolon, or tab
- Cell length exceeds max_cell_length setting — flagged as violation
- Numeric values outside specified minimum/maximum range — flagged in report
- Empty CSV input — returns error
- Malformed CSV with unmatched quotes — parse error returned
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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