Screenshot Critique

Screenshot Critique

Use an unprimed sub-agent as a second set of eyes before accepting visual work. This is for visual defects, not pixel metrics; pair it with compare-screenshots when you also need numbers — including on a single shot with nothing to compare against, whose scene metrics say whether the frame has any content in it at all.

Workflow

1. Capture or locate the exact PNGs/GIF frames under review.
2. Keep native-size evidence and create supplementary 2x-4x crops for every key feature, plus the full screenshot. Include complete endpoints and fades; recheck crop bounds after geometry changes. Crop selected units, city/town stacks, flags/poles, shadows, selection rings, labels/icons, roads, terrain features, water, and any artifact-prone area. If the complaint is about "too faint", "wrong order", or "not in perspective", the crop is mandatory.
3. Spawn one fresh explorer with fork_context: false; pass only the full images, the crops, and a short neutral task. Include the approved reference and user requirements when judging fidelity; withhold history, implementation details, prior verdicts and the expected answer.
4. Ask for concrete visible defects with confidence levels. Name likely risk categories: unit/prop depth ordering, layering, shadows, selection-marker contrast, ground-plane perspective, flag/pole attachment, label style and icon readability, blur, scale, lighting, artifacts, missing models, terrain feature readability, roads, water, and overall scan readability.
5. Compare the sub-agent's critique against your own inspection. Treat overlap as high-priority evidence. Treat novel high-confidence findings as bugs to inspect, not as taste notes to dismiss.
6. Record actionable findings in the spec, visual report, or next task plan before claiming the screenshot is accepted.

Sub-Agent Prompt

Use this shape, replacing the bracketed surface and attaching local images:

Fresh visual critique task. You have no project backstory and should only
inspect the supplied screenshots and crops. First inspect the full screenshot
for context, then inspect each crop at zoomed scale. Look for concrete
visual/layout defects in [surface], especially unit/prop depth ordering,
layering, shadows, selection-marker contrast, ground-plane perspective,
flag/pole attachment, label style/icons, blur, scale, lighting, artifacts,
missing models, terrain feature readability, roads, water, and scan
readability. Do not assume these are correct. Return a concise list of issues
you can see, with confidence and whether the issue is visible in the full image,
the crop, or both.

Spawn config:

• agent_type: explorer
• fork_context: false
• attach screenshots as local_image items
• omit model overrides unless the user explicitly requests one

Rules

• Mandatory before "fixed": never declare a user-reported visual bug fixed on your own inspection — your eyes are primed by the fix you just made. Run the unprimed critique on the candidate shot first; "mild residue" you are tempted to wave through is exactly what it exists to catch. (Recorded failure: a "fixed" sky that an unprimed agent identified as the terrain mesh's underside filling the entire sky region.)
• Reproduce the reporter's framing. When the user supplied a screenshot, the critique must include a capture at that framing (same camera/zoom/spot, or as close as reproducible) — a defect that lives at their framing can be invisible at yours. Your chosen probe framing is a supplement, never the substitute.
• Prove the change is real before critiquing it. Byte/pixel-diff the candidate against the pre-change baseline first: a critique of an unchanged image "verifies" a no-op. (Recorded failure: a palette pass that never reached the production render path — before/after were byte-identical and only the diff caught it.)
• Hand over the complete capture set, never a curated one. Every state you captured, every viewport, desktop and mobile. Choosing which shots to show is the same bias the fresh pass exists to remove: you will pick the ones you already believe are fine, and the weak state is exactly the one that gets left out. If a state is hard to reach by hand, drive it deterministically and capture it rather than omitting it.
• When no sub-agent is available, argue the other side yourself. For each feature under judgment, write one sentence making the strongest case that it is broken, citing only what is visible in the shot — then decide. Writing the case first is what makes it adversarial; deciding first and justifying after is the primed inspection this skill exists to replace. Include those sentences in the report so the reasoning is reviewable.
• Never tell the sub-agent the defect you expect it to find.
• Use the current candidate screenshot, not a stale report or baseline image.
• Do not rely on full-page report scale for small visual features. Attach crops around the exact features a player would read: selected army/city, label/icon clusters, flags, shadows, ring edges, road crossings, terrain feature patches, water labels, and suspicious debug/artifact regions.
• If the sub-agent says a crop reveals an issue that is weak or invisible in the full shot, treat it as a real usability defect when the player can zoom to that scale in-game.
• For animation, attach a short set of deterministic still frames first; GIFs are useful for human review, but still frames make specific defects easier to name.
• A passing headline does not erase a reported small mismatch or uncertainty. Resolve it using Reference Landmarks; a second opinion does not replace direct inspection or regression gates.
• If the sub-agent catches an issue the main agent missed, add that failure mode to the relevant feature plan or visual checklist immediately.