Content
55%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 body is concise and cleanly organized but stays at the level of describing what the agent does rather than instructing how, lacking executable steps and a validation loop for offline/fallback handling.
Suggestions
Add a concrete, executable workflow: specify the search query construction, the DuckDuckGo scrape command/endpoint, and how results are parsed and limited to 1-5.
Add a validation checkpoint after fetching (e.g., verify results exist, label and load curated fallback data only when web access fails) so the fetch-then-fallback loop is explicit.
Move or point to the curated fallback dataset with a concrete path or reference so the fallback mechanism is actionable rather than implied.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Lean and efficient body with no padding; it assumes Claude's competence and every line earns its place. | 5 / 5 |
Actionability | Provides only high-level hints ('Search the web', 'Extract and summarize relevant findings') with no concrete commands, endpoints, or executable steps; the DuckDuckGo scrape mechanism is mentioned but not specified. | 2 / 5 |
Workflow Clarity | Lists capabilities and guardrails as bullets but has no sequenced workflow and no validation checkpoints for a fetch operation that risks returning nothing or fabricated data. | 2 / 5 |
Progressive Disclosure | Well-organized with clear 'Skills' and 'Guardrails' sections and no bundle files to over-structure; appropriate for a short skill, though the fallback/curated data source is referenced but not separated into a file. | 4 / 5 |
Total | 13 / 20 Passed |