Content
85%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The body is lean, actionable, and well-organized with executable code and clear design rationale. Its one gap is the absence of an explicit cache validation/freshness checkpoint in the read workflow.
Suggestions
Add an explicit validation step in read_cache or the service layer, e.g. verify the cached document's source_path still exists or that the stored hash matches before trusting a hit.
Include a brief cache-warm/cold-run verification note (e.g. run twice and confirm the second run logs a cache hit) so Claude can confirm the pipeline works end-to-end.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Lean and efficient: it jumps straight into the pattern with executable code and tight rationale tables, assuming Claude's competence without explaining basic caching or hashing concepts. | 3 / 3 |
Actionability | Provides fully executable Python (compute_file_hash, read/write_cache, extract_with_cache) plus concrete design-decision and anti-pattern examples that are copy-paste ready. | 3 / 3 |
Workflow Clarity | The service-layer sequence (hash -> check cache -> miss -> extract -> write) is present, but this batch/caching workflow lacks an explicit validation checkpoint verifying cache integrity or freshness on read, which caps workflow clarity at 2. | 2 / 3 |
Progressive Disclosure | Well-organized into clearly signaled sections (Core Pattern steps, Key Design Decisions, Best Practices, Anti-Patterns, When to/Not to Use) with no bundle files needed; everything is one well-structured level. | 3 / 3 |
Total | 11 / 12 Passed |