component-split-ocr-review

name	component-split-ocr-review
description	Export deterministic component-level OCR evidence for one transparent or semi-transparent image by splitting alpha-connected components, writing a component table, and running OCR on each component. Use when bounded component evidence must be exported before any downstream refinement or caption rerun.

Component Split OCR Review

Overview

Use this skill to turn one local image into a bounded review surface:

• alpha-connected component crops
• component summary table
• per-component OCR evidence
• markdown and JSON artifacts for human review

This skill wraps the shared component split/OCR builder. It does not own semantic object selection, imagegen repair, or caption regeneration.

Use This Skill When

• one local image already exists
• the image is transparent or semi-transparent, or at least worth checking for alpha-separated parts
• a human needs to inspect component-level slices before deciding what to keep
• OCR on each separated component is useful evidence

Do Not Use This Skill When

• the task is full-image caption generation
• semantic object isolation or model-assisted correction is the current task
• batch subset triage across many images is the current task
• final image approval or rename/metadata commit is the current task
• the underlying tool lifecycle is broken — route to vendored-mcp-onboarding

Required Inputs

• one absolute or repo-relative --image-path
• optional --output-root
• optional --alpha-threshold
• optional --min-pixels
• optional --padding
• optional --min-components-for-success

Script

• scripts/build_component_split_ocr_report.py

References

• knowledge_bases/component-split-ocr-review-knowledge-base-at2026-03-28-01-20.md
• references/runtime.md
• references/troubleshooting.md

Workflow

1. Confirm the target is one bounded local image.
2. Run the skill-local wrapper, not a handwritten ad hoc command.
3. Let the shared builder perform alpha split first.
4. Use the generated component table and per-component OCR as the review surface.
5. Treat the output as review evidence only until a human decides what components are meaningful.
6. Promote only reviewed components into later object-isolation or caption flows.

Preferred Output Surface

• default output root: control/project_domain/archive/component_split_ocr/
• one bounded subdirectory per source dataset and image stem
• keep review artifacts in project_domain/runs, not user_decisions, until a decision is explicitly promoted

Outputs

• COMPONENT_SPLIT_OCR_REPORT.md
• COMPONENT_SPLIT_OCR_REPORT.json
• alpha_components/*.png
• component_ocr/*_OCR_RESULT.json

Known Good Fit

• transparent PNGs with disconnected visual parts
• slide-export images where alpha-separated icons or panels need inspection
• weak semantic isolation cases where deterministic component evidence is needed first

Not Owned Here

• semantic object selection
• imagegen correction
• full-image caption rerun
• batch triage across directories
• final approval or commit
• component evidence를 multimodal loop state로 재주입하거나 refinement할 때 → multimodal-evidence-refinement-loop
• review surface 정규화 및 manifest split이 필요할 때 → image-text-cot-review
• tool lifecycle integrity (launcher, registration, inventory, setup state)