Content
77%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The content is highly actionable with a well-sequenced, validated workflow, but it is verbose due to repeated fetcher-resolution boilerplate and explanatory asides. Progressive disclosure is moderate since everything lives inline with no real bundle references.
Suggestions
Factor the repeated $ARIS_REPO + fetcher resolution logic into a single shared snippet or helper reference instead of duplicating it across the arXiv, Semantic Scholar, DeepXiv, Exa, and download blocks.
Remove or shorten rationale asides Claude already knows (e.g., 'Why use Semantic Scholar?') to improve token efficiency, or move them to a one-level-deep reference file.
Move the full Source Table and detailed per-source bash recipes into a references/ file (e.g., DATA_SOURCES.md) linked from the main body, keeping SKILL.md as a lean overview with one-level-deep navigation.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is mostly operational but carries repeated near-identical $ARIS_REPO/$FETCHER resolution boilerplate across five bash blocks and explanatory asides Claude already knows ('Why use Semantic Scholar? Many IEEE/ACM journal papers are not on arXiv'), so it could be tightened. | 2 / 3 |
Actionability | It provides concrete, executable bash blocks with real commands, specific MCP tool patterns, exact API field lists, and glob patterns that are copy-paste ready, matching the score-3 anchor. | 3 / 3 |
Workflow Clarity | Steps 0a–0c and 1–6 are clearly sequenced with explicit validation/checkpoints (stop-and-ask on missing requested sources, verify PDF > 10 KB, de-duplicate between sources, graceful skip of unrequested sources), giving clear feedback loops. | 3 / 3 |
Progressive Disclosure | No bundle files exist and the only external reference (shared-references/integration-contract.md) sits outside the bundle; the large source table and repeated bash blocks are inline rather than split into one-level-deep references, so structure is present but could be better organized. | 2 / 3 |
Total | 10 / 12 Passed |