Content
71%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 well-organized, actionable skill body with a clear phased workflow, strong terminal-review feedback loops, and exemplary progressive disclosure via verified one-level references. Its main weakness is conciseness — directory conventions and constraints are restated across multiple sections and could be consolidated.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is information-dense and avoids teaching Claude what a LaTeX paper is, but it is long (250+ lines) with repeated restatements of the same directory conventions and constraints across multiple sections, so it could be tightened. | 3 / 5 |
Actionability | Concrete, runnable guidance is present (the exact prepare_workspace.py command with flags, an explicit default section ordering block, specific build-chain fallback list), with only minor gaps such as config.yaml keys being referenced without inline values. | 4 / 5 |
Workflow Clarity | A clear phased sequence (阶段 0–5) with explicit terminal review checkpoints (section-role-check, full-consistency review, logic-tree review) and re-review-on-blocker feedback loops; minor gaps in per-step validation keep it just below 5. | 4 / 5 |
Progressive Disclosure | Excellent one-level-deep structure: the body is an overview with well-signaled references to real files in references/ and references/templates/ (all verified present), with explicit 'read on demand' guidance keyed to task type and no nested multi-hop references. | 5 / 5 |
Total | 16 / 20 Passed |