算法艺术创作
algorithmic-art
通过代码和可调参数创作生成艺术与交互式视觉效果。
skill-comply【设计与创意】Visualize whether skills, rules, and agent definitions are actually followed — auto-generates scenarios at 3 prompt strictness levels, runs agents, classifies behavioral sequences, and reports compliance rates with full tool call timelines
独立 GitHub 快照 · 自动分类 · 以原作者文档为准
Measures whether coding agents actually follow skills, rules, or agent definitions by:
codex -p and capturing tool call traces via stream-jsonskills/*/SKILL.md): Workflow skills like search-first, TDD guidesrules/common/*.md): Mandatory rules like testing.md, security.md, git-workflow.mdagents/*.md): Whether an agent gets invoked when expected (internal workflow verification not yet supported)/skill-comply <path># Full run
uv run python -m scripts.run ~/.codex/rules/common/testing.md
# Dry run (no cost, spec + scenarios only)
uv run python -m scripts.run --dry-run ~/.codex/skills/search-first/SKILL.md
# Custom models
uv run python -m scripts.run --gen-model fast --model standard <path>
Measures whether a skill/rule is followed even when the prompt doesn't explicitly support it.
Reports are self-contained and include:
For users familiar with hooks, reports also include hook promotion recommendations for steps with low compliance. This is informational — the main value is the compliance visibility itself.