Content
77%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This is a well-structured, highly actionable onboarding skill with clear phase sequencing, concrete tool calls, and good validation checkpoints. Its main weakness is length — the dual-path structure (testing + observability) makes the single file quite long, and some sections include explanatory context that Claude doesn't need. The progressive disclosure to specialized skills is good, but the body itself could benefit from splitting the two paths into separate referenced files.
Suggestions
Consider splitting the testing path (Phases 3-6) and observability path (Phases 3-7) into separate referenced files to reduce the main SKILL.md length and improve progressive disclosure.
Trim explanatory framing like 'Use this for pre-deploy regression testing and is my prompt change safe to ship?' and project organization guidance — Claude can infer these from context.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is quite long (~400 lines) and includes some explanatory framing that Claude doesn't need (e.g., explaining what observability is, what testing is, project organization guidance). However, most content is actionable and path-specific, so it's not egregiously padded — just could be tightened in several places. | 2 / 3 |
Actionability | The skill provides concrete tool names, executable JSON payloads, specific API endpoints, exact field names, valid role values, and clear instructions for each step. It names the exact tools to call (e.g., `observe_create`, `scenarios_agent_create`, `call_logs_evaluate_metrics_create`) with copy-paste-ready payloads. | 3 / 3 |
Workflow Clarity | The multi-phase workflow is clearly sequenced with explicit phase boundaries, a state assessment step before starting, validation checkpoints (verify ingestion, confirm API key works, poll for generation progress, re-retrieve for evaluation status), and error recovery guidance (fix and retry on tool failure). The decision table for state assessment is particularly well-structured. | 3 / 3 |
Progressive Disclosure | The skill references specialized skills (cekura-create-agent, cekura-metric-design, cekura-eval-design, cekura-metric-improvement) and external docs appropriately, but the body itself is very long with substantial inline content that could be split. It references `references/api-quickstart.md` but no bundle files were provided, and the two-path structure creates a monolithic document that could benefit from separation. | 2 / 3 |
Total | 10 / 12 Passed |