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Repair Document Parsing, OCR & Extraction Failures
Repair Document Parsing, OCR & Extraction Failures is a bounded ToolForge Labs workflow.
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Repair Document Parsing, OCR & Extraction Failures
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Our ingestion pipeline accepts PDFs and office documents. Some scans return empty text, multi-column PDFs scramble reading order, tables lose row boundaries, and one malformed PDF can consume huge memory. Repair the parsing/extraction contract without sending documents to new external services.
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- Compiled the repair document parsing
The likely issue is a contract mismatch around PDF/document parsing, OCR handoff, page ordering, text extraction, tables, encodings, malformed files, resource limits, metadata, partial results, and provenance. I would first define the invariant: Every extracted fragment must retain source provenance and extraction status; unsupported, malformed, image-only or partially parsed content must be explicit rather than silently represented as complete text. Then I would trace the smallest owning boundary, apply or propose a bounded repair/review step, and add deterministic normal, boundary, failure and replay tests. The workflow preserves document confidentiality, sandbox/resource limits, accepted file formats, provenance requirements, and downstream data contracts. If repository/workspace files are available, the findings can be mapped to exact paths and focused local validation; with partial evidence, the result stays an explicit diagnosis/evidence map with assumptions and no invented execution claims.
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About this skill
Repair Document Parsing, OCR & Extraction Failures is a bounded ToolForge Labs workflow. Diagnose, review, and repair PDF/document parsing, OCR handoff, page ordering, text extraction, tables, encodings, malformed files, resource limits, metadata, partial results, and provenance. Works from full repositories/workspaces or partial evidence. Produces bounded fixes or evidence gates with deterministic validation while preserving existing product/security policy and avoiding invented execution claims. It works from a full repository/workspace or partial evidence such as snippets, logs, configuration, traces, documents, tickets, and architecture notes. The skill separates verified facts from assumptions, avoids invented execution claims, and produces concrete repair/review steps with focused deterministic validation or traceable evidence.
Find more skills like this on the Claude Skills Marketplace, the Codex Skills Marketplace and the Gemini Skills Marketplace, or browse Claude Skills for APIs & Backend.
Cannot verify fixes on production environments. Requires local workspace access or specific snippets to perform implementation edits.
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Use a clean branch or controlled review workspace. Supply repository/workspace files, logs, traces, configuration, documents, or evidence needed for the task. Review patches/findings before merge or operational action; keep production credentials and destructive production actions out of the workflow.