Content
81%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-structured, highly actionable multi-phase workflow with strong validation feedback loops and sound progressive disclosure; its main weakness is moderate verbosity from repeated justifications and inline prompt templates that could be externalized.
Suggestions
Trim repeated justification prose (e.g., the annotation-file rationale and reiterated 'real data only' / 'let the data lead' notes) — state the rule once.
Move the full extraction and reduction prompt templates into a reference file and link to them from the body, which would improve both conciseness and progressive disclosure.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is mostly efficient operational detail, but it includes unnecessary explanation (e.g., justifying why annotation files are redundant, repeated restatements of 'let the data lead' / 'real data only') and long inline prompt templates that could be tightened or moved out. | 3 / 5 |
Actionability | Provides fully copy-paste-ready extraction and reduction prompts, exact output file paths, versioned naming schemes, dataset-size batching thresholds, and platform-branched stat commands — concrete and executable across the common cases. | 5 / 5 |
Workflow Clarity | A clear six-phase sequence (0–6) with explicit validation checkpoints (verify counts match inventory, re-launch short/timeout batches, fall back when no denied plans) and feedback loops for the batch extraction operation. | 5 / 5 |
Progressive Disclosure | The body acts as an overview with clearly signaled, one-level-deep references that all exist (fallback reference, parser script, HTML template), though the long reduction-prompt section list and prompt templates are inlined rather than split into a reference. | 4 / 5 |
Total | 17 / 20 Passed |