Content
93%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 a tight, executable reference: lean prose, copy-paste code for the main streaming patterns, a useful decision tree, and a well-structured references section pointing to real bundle files. The only gap is the absence of explicit validation/feedback checkpoints, which is less critical for this non-destructive reference skill.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The body is lean and assumes Claude's competence — a one-line overview, executable code blocks, and a gotchas list with no padding or explanation of basic streaming concepts, matching the anchor 5 example. | 5 / 5 |
Actionability | Multiple copy-paste-ready TypeScript/TSX blocks cover the common cases (custom response with tool calls, useLocalRuntime fetch loop, debugging decode loop) plus an install command and concrete gotcha fixes. | 5 / 5 |
Workflow Clarity | The 'When to Use' decision tree gives clear routing between the Vercel AI SDK and custom assistant-stream paths and sections are well organized, but as a reference-style skill it lacks explicit validation checkpoints, keeping it just below anchor 5. | 4 / 5 |
Progressive Disclosure | A concise overview points to three real, one-level-deep reference files (data-stream.md, assistant-transport.md, encoders.md), each labeled with a one-line description, matching the anchor 5 clear-overview-with-well-signaled-references pattern. | 5 / 5 |
Total | 19 / 20 Passed |