Content
87%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
The body is concise, actionable, and well-organized with copy-paste-ready commands, but it lists commands in isolation rather than as a sequenced workflow with validation checkpoints for multi-agent management operations.
Suggestions
Add a sequenced workflow with explicit validation checkpoints (e.g., doctor -> start -> verify via 'monitor --follow' -> assign) instead of presenting commands as an unsequenced list.
Include a feedback loop for start/assign operations (confirm the agent session is running and check logs for errors before proceeding), since managing multiple agents is a batch-like operation that benefits from verification.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is lean (~40 lines) with no re-explanation of concepts Claude already knows and no padding; every section (When to Use, Prerequisites, Common commands, Notes, Limitations) earns its place. | 3 / 3 |
Actionability | Provides fully executable, copy-paste-ready commands (e.g., 'python3 agent-manager/scripts/main.py start EMP_0001') including a concrete heredoc-based assign example, matching the anchor for executable code with specific examples. | 3 / 3 |
Workflow Clarity | Commands are presented individually rather than as a sequenced workflow, and there are no validation/verification checkpoints for the batch-like operations of starting, assigning, and monitoring multiple agents, capping workflow clarity at 2 per the guidelines. | 2 / 3 |
Progressive Disclosure | At under 50 lines with no need for external reference files (none exist in references/scripts/assets), the well-organized sectioned structure satisfies the simple-skill allowance for a top score in progressive disclosure. | 3 / 3 |
Total | 11 / 12 Passed |