Content
78%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 content is well-structured and actionable: a command quick-reference, a workflow graph, common mistakes, and pipeline context, with detail correctly offloaded to two real reference files. It is just shy of perfect only because a copy-paste example invocation and an explicit validation checkpoint would push actionability and workflow clarity to the top anchor.
Suggestions
Add one copy-paste example invocation (e.g. `$PYTHON_PATH .agentsociety/bin/ags.py use-dataset search --category surveys`) to make the quick reference immediately runnable.
Make the post-download validation explicit in the workflow (e.g. 'After download, run info <id> to confirm version matches remote') to add a clear checkpoint.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is lean: a quick-reference command table, a dot-graph workflow, a common-mistakes table, and pipeline position, with no padding explaining what datasets are. Only minor tightening opportunities remain. | 4 / 5 |
Actionability | Provides a concrete command table with real subcommands and flags plus the exact invocation path '.agentsociety/bin/ags.py'; fully actionable, though a single copy-paste example invocation line would make it copy-paste ready. | 4 / 5 |
Workflow Clarity | A clear browse→readme→download→inspect→update sequence is shown via the dot graph, with the Common Mistakes table functioning as implicit checkpoints (read README first, check for updates). No explicit validate→fix→retry loop, but the operations are low-risk so checkpoints are adequate. | 4 / 5 |
Progressive Disclosure | SKILL.md is an overview that clearly signals one-level-deep references to real files (references/listing-guide.md and references/metadata-format.md), keeping detailed material out of the main body with easy navigation. | 5 / 5 |
Total | 17 / 20 Passed |