Content
85%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.
The body is a well-structured JIT workflow: a sequenced 7-step process with explicit validation and iteration, concrete commands, and bulk detail offloaded to real one-level-deep reference/script bundles. Minor conciseness trimming and inlining key template specifics would push it higher.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Efficient and mostly lean with checklists, tables, and concrete commands rather than re-explaining known concepts; minor padding in the 'Key advantages' marketing bullets and repeated Output lines could be trimmed. | 4 / 5 |
Actionability | Provides concrete, executable commands (cat references/*, python3 scripts/test_glob_pattern.py --pattern ..., validation scripts) and a final checklist; the populated template specifics live in the referenced files rather than inline, leaving minor gaps. | 4 / 5 |
Workflow Clarity | A clear 7-step sequence with an explicit Step 6 validation checkpoint (YAML validation, glob testing, rule-specificity checks), a final checklist, and a Step 7 feedback/refinement loop for error recovery. | 5 / 5 |
Progressive Disclosure | Clear overview with well-signaled one-level-deep references (cat references/...) and a Resources section listing each reference/script with its purpose; all referenced bundle files (scope_analysis_checklist, pattern_construction, rule_discovery_checklist, template_examples, context_economics, test_glob_pattern.py) exist. | 5 / 5 |
Total | 18 / 20 Passed |