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GitHub リポジトリ

RewardHarness

RewardHarness には TIGER-AI-Lab から収集した 76 個の skills があり、リポジトリ単位の職業カバレッジとサイト内 skill 詳細ページを表示します。

収集済み skills
76
Stars
14
更新
2026-05-16
Forks
1
職業カバレッジ
15 件の職業カテゴリ · 100% 分類済み
リポジトリエクスプローラー

このリポジトリの skills

instruction-following-completeness
データサイエンティスト

Score completeness of instruction execution. Partial edits get partial credit; missed sub-steps cost points.

2026-05-16
realism-and-artifact-penalties
データサイエンティスト

Guidance on penalizing artifacts while allowing conceptual unrealism if requested by the prompt.

2026-05-16
text-and-ocr-analyzer
データサイエンティスト

Extracts and analyzes text within images to verify spelling, placement, and clarity.

2026-05-16
evaluating-background-changes
データサイエンティスト

Guidelines for evaluating background replacements and scene changes.

2026-05-14
evaluating-multi-step-edits
データサイエンティスト

Guidelines for evaluating prompts with multiple distinct instructions.

2026-05-14
evaluating-object-replacements
卸売・小売バイヤー(農産物除く)

Guidelines for evaluating object replacements and modifications.

2026-05-14
evaluating-style-transfers
データサイエンティスト

Guidelines for evaluating artistic style transfers.

2026-05-14
evaluating-text-rendering
グラフィックデザイナー

Guidelines for evaluating text additions and modifications in images.

2026-05-14
compare-images
データサイエンティスト

Compare a source image and edited images to identify differences, check if instructions were followed, and assess visual quality.

2026-05-14
artifact-and-structure-preservation
データサイエンティスト

Rules for prioritizing image integrity and penalizing severe artifacts or loss of original structure.

2026-05-14
artistic-and-cultural-references
アートディレクター

Guidelines for evaluating prompts that reference specific artists, art styles, or cultural phenomena.

2026-05-14
embrace-intended-drastic-changes
データサイエンティスト

Rules for evaluating setting and style changes, strictly forbidding penalizing an image for losing original context when a new setting is requested.

2026-05-14
enforce-logical-consistency
データサイエンティスト

Ensures the reasoning chain does not contain internal contradictions between stated facts and image evaluations.

2026-05-14
entity-definition-activation
データサイエンティスト

Requires explicitly defining specific artists, styles, or entities and their visual hallmarks before evaluating.

2026-05-14
environmental-blending-and-lighting-adaptation
データサイエンティスト

Rules for evaluating background changes, rewarding necessary adaptations to the subject's lighting, shadows, and ground contact.

2026-05-14
evaluate-insertions-and-anatomical-integrity
特殊効果アーティスト・アニメーター

Guidelines for evaluating inserted humans, animals, or objects, prioritizing anatomical correctness over superficial integration.

2026-05-14
evaluate-physical-plausibility
データサイエンティスト

Guidelines for evaluating inserted or replaced objects for physical plausibility, penalizing floating objects or gravity-defying placements.

2026-05-14
evaluate-text-additions
データサイエンティスト

Guidelines for evaluating text additions, strictly prioritizing exact string matches and legibility over natural integration.

2026-05-14
holistic-evaluation-vs-tunnel-vision
ソフトウェア品質保証アナリスト・テスター

Prevents tunnel vision on specific requested edits by enforcing holistic evaluation, penalizing collateral damage, anatomical distortion, and loss of original context.

2026-05-14
instruction-over-naturalness
データサイエンティスト

Prioritizes instruction fulfillment over naturalness, warning against the 'subtlety trap' and 'preservation bias'.

2026-05-14
mitigate-positional-bias
データサイエンティスト

Strategies to prevent defaulting to Image B and ensure fair evaluation of both images.

2026-05-14
object-replacement-proportions-and-exaggeration
ウェブ・デジタルインターフェースデザイナー

Guidelines for evaluating object replacements where the new object is inherently bulkier or different in proportion (e.g., snow goggles vs glasses).

2026-05-14
overcoming-default-to-a-bias
データサイエンティスト

Strategies to combat the strong bias of defaulting to Image A by hallucinating details or overvaluing naturalness.

2026-05-14
penalize-gibberish-text
データサイエンティスト

Guidelines for penalizing gibberish text, establishing that instruction fulfillment strictly outweighs text artifacts.

2026-05-14
penalize-unintended-style-changes
アートディレクター

Guidelines for penalizing images that alter the original art style when not requested, with exceptions for intended drastic changes.

2026-05-14
preserve-subject-interaction-and-pose
その他心理士

Guidelines for preserving realistic interaction and strict anatomical integrity when an object is replaced.

2026-05-14
prevent-image-feature-swapping
データサイエンティスト

Mandates strict verification of which image contains which features to prevent attributing Image A's details to Image B.

2026-05-14
reasoning-preference-alignment
データサイエンティスト

Ensures the final preference logically matches the comparative analysis in the reasoning chain.

2026-05-14
strict-semantic-and-conceptual-alignment
データサイエンティスト

Ensures strict adherence to requested concepts, rejecting semantic near-misses (e.g., classroom vs cafeteria).

2026-05-14
subject-vs-setting-modifications
特殊効果アーティスト・アニメーター映画・ビデオ編集者

Guidelines for preserving the main subject during setting changes, penalizing subject destruction.

2026-05-14
verify-extreme-claims-and-hallucinations
データサイエンティスト

Guidelines to prevent hallucinating extreme failures (e.g., 'blank black screen') and ensure logical consistency.

2026-05-14
verify-instruction-target-and-spatial-relations
ソフトウェア品質保証アナリスト・テスター

Ensures edits are applied to the exact target, strictly enforcing spatial prepositions (under, behind) and prioritizing correct placement over natural integration.

2026-05-14
object-locator-and-counter
データサイエンティスト

Detects, counts, and locates specific objects in the image, useful for instructions targeting a specific instance (e.g., 'the 4th surfboard').

2026-05-14
side-by-side-image-comparator
データサイエンティスト

Compares two images side-by-side to definitively determine which image contains specific objects, text, or features, preventing feature-swapping.

2026-05-14
text-and-spelling-checker
編集者

Extracts and verifies text in the image, checking for exact string matches, spelling errors, and legibility.

2026-05-14
visual-detail-and-setting-analyzer
データサイエンティスト

Analyzes images to verify exact settings (e.g., cafeteria vs classroom), fine-grained details, and extreme artifacts.

2026-05-14
visual-question-answering
データサイエンティスト

Answers specific visual questions about the images to verify the presence of objects, text, spatial relations, or specific attributes.

2026-05-14
evaluating-multiple-constraints
データサイエンティスト

How to systematically evaluate prompts with more than one instruction.

2026-05-14
evaluating-style-transfers
データサイエンティスト

Guidelines for evaluating artistic style transfers and thematic changes.

2026-05-14
evaluating-text-additions
データサイエンティスト

Guidelines for evaluating the addition or modification of text in images.

2026-05-14
このリポジトリの収集済み skills 76 件中、上位 40 件を表示しています。