Content
100%Reviews 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-organized, actionable CLI reference with executable commands, a sequenced workflow that includes verification and error recovery, and clean one-level-deep references to real bundle files. It is token-efficient without sacrificing clarity.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is a dense, table-driven CLI reference with no concept padding Claude already knows; every section (Quick Reference, Parameters, Index Contract, Common Mistakes) earns its place. Not 2 because there is no fluff or unnecessary explanation, only minor redundancy between the Quick Reference and full-text helper tables. | 3 / 3 |
Actionability | Commands like `$PYTHON_PATH .agentsociety/bin/ags.py literature-search "query" --year-from 2020 --year-to 2024` are fully executable, with exact env var names and flag tables — copy-paste ready. Not 2 because guidance is concrete and complete rather than pseudocode. | 3 / 3 |
Workflow Clarity | The 8-step Recommended Workflow is clearly sequenced with a precondition check (confirm `.env`), a verification step (inspect `papers/literature_index.json` after completion), and an error-recovery fallback (failed PDFs → Optional Full-Text Retrieval plus the Common Mistakes table). Not 2 because validation/verification checkpoints are present for this batch download operation. | 3 / 3 |
Progressive Disclosure | The overview points to one-level-deep references (`references/data-sources.md`, `references/full-text-retrieval.md`), both of which exist in the bundle and are clearly signaled inline and in a References section. Not 2 because content is appropriately split with easy navigation rather than dumped inline. | 3 / 3 |
Total | 12 / 12 Passed |