JSONL Lint and Repair

Store Positioning

Store title: JSONL Lint and Repair

Short description: Lint JSONL files line by line, detect malformed records and schema issues, optionally repair safe common problems, and output cleaned JSONL plus detailed line-level diagnostics.

SEO title: JSONL Lint and Repair — data QA, validation, and cleanup utility

SEO description: Lint JSONL files line by line, detect malformed records and schema issues, optionally repair safe common problems, and output cleaned JSONL plus detailed line-level diagnostics. Use it to validate rows, schemas, duplicates, field quality, and delivery-readiness before handing data to clients or automations.

Categories: SEO_TOOLS, DEVELOPER_TOOLS

Keywords: jsonl, lint, repair, schema, data/schema qa utility

Pay-Per-Event Pricing

This actor uses pay-per-event pricing. Event prices include Apify platform usage; users are not expected to pay a separate platform-usage pass-through charge for the configured pricing model.

• Tier: U2 — Data/schema QA utility
• Primary event: record-profiled at $0.00390 base
• Default max charge: $5.00
• Store discounts: FREE/BRONZE base, SILVER discounted, GOLD deepest approved discount

Event set:

• actor-start: base $0.00500, GOLD $0.00400. Jsonl Lint And Repair: charged when actor start is completed. The price includes Apify platform usage; no separate usage pass-through is intended.
• record-profiled: base $0.00390, GOLD $0.00312. Jsonl Lint And Repair: charged when record profiled is completed. The price includes Apify platform usage; no separate usage pass-through is intended.
• issue-detected: base $0.00372, GOLD $0.00298. Jsonl Lint And Repair: charged when issue detected is completed. The price includes Apify platform usage; no separate usage pass-through is intended.
• qa-report-generated: base $0.05000, GOLD $0.04000. Jsonl Lint And Repair: charged when qa report generated is completed. The price includes Apify platform usage; no separate usage pass-through is intended.

Public Task Concepts

• Audit JSONL Lint and Repair controls on a capped public sample
• Find high-priority JSONL Lint and Repair issues before release
• Validate JSONL Lint and Repair evidence from supplied pages
• Prioritize JSONL Lint and Repair fixes with severity and proof
• Export JSONL Lint and Repair QA rows for client review

Lints JSON Lines record by record, preserving line numbers and previews while detecting invalid JSON, blank lines, missing fields, type mismatches, duplicates, oversized rows, and safe repairs.

Inputs

• jsonlTextInputs
• jsonlUrls
• expectedSchema
• requiredFields
• idField
• repairMode
• allowedRepairs
• strictMode
• maxLines
• maxLineBytes
• includeRepairedOutput
• timeoutMs
• maxChargeUsd

Public source provenance

The starter input uses bounded public records from the GitHub user endpoints for octocat, defunkt, and mojombo. The checked-in projection keeps exact runs deterministic and avoids sending credentials or private data. Live URL inputs remain available when a current network check is required.

Outputs

Dataset fields: sourceId, lineNumber, issueCode, severity, originalLinePreview, parsed, schemaValid, fieldPath, expectedType, actualType, repairApplied, repairedLine, duplicateGroupId, recommendation.

Reports: jsonl-lint-report.md, repaired-output.jsonl, invalid-lines.csv, jsonl-schema-violations.json, jsonl-repair-log.json.

Use small capped runs first; live network checks should stay bounded and avoid secrets in inputs.

Live and local execution use the same pay-per-event billing guard: the actor-start event is accepted before analysis, each paid row is charged before dataset output, reports are charged before key-value-store output, and maxChargeUsd stops gracefully without leaking unpaid artifacts.