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qa-rasmapper-web-parity

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Atualizado16 de julho de 2026 às 15:15

Create deterministic paired RASMapper and RAS Commander MapLibre evidence bundles from one review specification. Use when comparing a HEC-RAS model in RASMapper with its web viewer, validating map/tree/legend fidelity on desktop and mobile, checking nodata/extent/default layers, or establishing visual regression fixtures with fixed numeric COG probes.

Instalação

Instalar com Codex ou Claude Copie este prompt, cole no Codex, Claude ou outro assistente e deixe que ele revise a página da skill e instale para você.

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gpt-cmdr

gpt-cmdr/ras-commander

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Ocupações relacionadasSOC

Baseado na classificação ocupacional SOC

Analistas de garantia de qualidade de software e testadoresInformática e Matemática·SOC 15-1253

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SKILL.md

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name	qa-rasmapper-web-parity
shared_corpus	true
harness_scope	shared
source_owner	gpt-cmdr
security_review	internal
description	Create deterministic paired RASMapper and RAS Commander MapLibre evidence bundles from one review specification. Use when comparing a HEC-RAS model in RASMapper with its web viewer, validating map/tree/legend fidelity on desktop and mobile, checking nodata/extent/default layers, or establishing visual regression fixtures with fixed numeric COG probes.

RASMapper Web Parity

Use one YAML/JSON review specification for both capture surfaces. Keep map, tree, legend, semantic assertions, and numeric probes as separate evidence channels.

Workflow

Read references/review-spec.md and validate project, manifest, CRS, layer IDs, profiles, viewport sizes, crop regions, and numeric probes.
Copy the source project to the review output. Never configure the original .rasmap.
Run scripts/rasmapper_web_parity.py rasmapper SPEC OUTPUT on a Windows HEC-RAS host.
Run scripts/rasmapper_web_parity.py web SPEC OUTPUT where Python Playwright and Chromium are installed, or use the in-app browser at the exact specified desktop/mobile viewports.
Run scripts/rasmapper_web_parity.py compare SPEC OUTPUT after all images exist.
Inspect comparison.json, findings.md, contact-sheet.png, and region images.

uv run python .claude/skills/qa-rasmapper-web-parity/scripts/rasmapper_web_parity.py `
  rasmapper scripts/example_library/fixtures/muncie-parity.yml working/muncie-parity

Capture Contract

RASMapper: call RasMap.create_spatial_review_package() with fixed outer-window dimensions, selected plan/layer, terrain, range/ramp, RAS version, and matching web manifest metadata.
Web: wait for window.__rasCommanderViewerInstances, apply WGS84 bounds and manifest layer state through that QA hook, enable every declared extent-colored raster, wait for MapLibre and all raster styling to become idle, require a content-only semantic tree with one disclosure control per collapsible node, then capture page, map, tree, and active legend separately at desktop and mobile sizes.
Comparison: crop only declared RASMapper regions; normalize dimensions; report global SSIM, normalized mean absolute error, and a diff image. Do not use full desktop chrome as a golden.
Numeric probes: sample authoritative numeric COGs with rasterio and compare to explicit expected values/tolerances. Never infer numeric correctness from image colors.

Classification

Confirmed: deterministic semantic assertion or numeric probe failure.
Likely: repeatable image/extent/legend mismatch that needs targeted numerical review.
Uncertain: missing capture, unstable external basemap, anti-aliasing, or an undeclared crop.

Always distinguish raw HDF computation-element values from RASMapper/RasProcess interpolated rasters. A screenshot regression is presentation QA, not hydraulic validation.

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name	qa-rasmapper-web-parity
shared_corpus	true
harness_scope	shared
source_owner	gpt-cmdr
security_review	internal
description	Create deterministic paired RASMapper and RAS Commander MapLibre evidence bundles from one review specification. Use when comparing a HEC-RAS model in RASMapper with its web viewer, validating map/tree/legend fidelity on desktop and mobile, checking nodata/extent/default layers, or establishing visual regression fixtures with fixed numeric COG probes.

RASMapper Web Parity

Use one YAML/JSON review specification for both capture surfaces. Keep map, tree, legend, semantic assertions, and numeric probes as separate evidence channels.

Workflow

Read references/review-spec.md and validate project, manifest, CRS, layer IDs, profiles, viewport sizes, crop regions, and numeric probes.
Copy the source project to the review output. Never configure the original .rasmap.
Run scripts/rasmapper_web_parity.py rasmapper SPEC OUTPUT on a Windows HEC-RAS host.
Run scripts/rasmapper_web_parity.py web SPEC OUTPUT where Python Playwright and Chromium are installed, or use the in-app browser at the exact specified desktop/mobile viewports.
Run scripts/rasmapper_web_parity.py compare SPEC OUTPUT after all images exist.
Inspect comparison.json, findings.md, contact-sheet.png, and region images.

uv run python .claude/skills/qa-rasmapper-web-parity/scripts/rasmapper_web_parity.py `
  rasmapper scripts/example_library/fixtures/muncie-parity.yml working/muncie-parity

Capture Contract

RASMapper: call RasMap.create_spatial_review_package() with fixed outer-window dimensions, selected plan/layer, terrain, range/ramp, RAS version, and matching web manifest metadata.
Web: wait for window.__rasCommanderViewerInstances, apply WGS84 bounds and manifest layer state through that QA hook, enable every declared extent-colored raster, wait for MapLibre and all raster styling to become idle, require a content-only semantic tree with one disclosure control per collapsible node, then capture page, map, tree, and active legend separately at desktop and mobile sizes.
Comparison: crop only declared RASMapper regions; normalize dimensions; report global SSIM, normalized mean absolute error, and a diff image. Do not use full desktop chrome as a golden.
Numeric probes: sample authoritative numeric COGs with rasterio and compare to explicit expected values/tolerances. Never infer numeric correctness from image colors.

Classification

Confirmed: deterministic semantic assertion or numeric probe failure.
Likely: repeatable image/extent/legend mismatch that needs targeted numerical review.
Uncertain: missing capture, unstable external basemap, anti-aliasing, or an undeclared crop.

Always distinguish raw HDF computation-element values from RASMapper/RasProcess interpolated rasters. A screenshot regression is presentation QA, not hydraulic validation.