Content
86%Weight 40%Scale 1-5Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
A tight, well-structured skill body: lean sections, an executable smoke test backed by a real starter asset, and a clean overview-to-bundle split. Weaknesses are minor — the workflow's validation is implicit rather than an explicit feedback loop, and a few conventions (thumbnail extraction, quality ladder commands) are stated as directions without commands.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Lean bullet-based sections with zero padding; it never explains concepts Claude already knows (no Manim tutorials, no library comparisons) and every line is operational guidance. Matches the 'every token earns its place' anchor. | 5 / 5 |
Actionability | Provides a copy-paste smoke-test command ('manim -ql assets/network_graph_scene.py NetworkGraphExplainer') and a real, verified starter file, plus concrete render conventions. Not 5 because much of the workflow is directional ('tighten typography, spacing, color, and pacing') and commands for thumbnail extraction or higher-quality renders are absent. | 4 / 5 |
Workflow Clarity | A clear 7-step sequence with implicit validation checkpoints ('render the smallest working version first', 'start with a low-quality smoke test render', 'only push to higher quality after composition and timing are stable'). Not 5 because there is no explicit validate-then-fix-then-retry feedback loop; not 3 because checkpoints are present and sequenced, not merely implied. | 4 / 5 |
Progressive Disclosure | SKILL.md is a well-organized overview and the concrete scene code is appropriately split into a single one-level-deep, clearly signaled reference ('Use [assets/network_graph_scene.py] as a starting point for network-graph explainers') that exists and is executable. This matches the anchor-5 pattern of a clear overview with well-signaled references. | 5 / 5 |
Total | 18 / 20 Passed |