BD jsonlines
Vovk.ts JSON Lines streaming — generator handlers (`function*`, `async function*`), the `iteration` validation option, `validateEachIteration`, the `JSONLinesResponder` manual API, progressive responses via `progressive()`, consuming streams from the RPC client (async iteration, `using`, `asPromise`, `onIterate`, `abortController`), and `VovkIteration` / `VovkYieldType` inference. Use whenever the user asks to stream data ("stream tokens", "SSE-like streaming", "server-sent events", "progressive response", "poll in a loop", "yield results as they arrive", "chat completion streaming", "JSON Lines", "JSONL", "async generator endpoint", "incremental response", "push updates to the client"). Does NOT cover procedure basics → hand off to `procedure` skill. Does NOT cover RPC client setup / `vovk generate` → hand off to `rpc` skill. Does NOT cover WebSockets / bidirectional realtime — that's outside Vovk's scope.
Promises to handle JSON Lines streaming with generators, iteration validation, JSONLinesResponder API, and progressive responses. Description cuts off mid-sentence, one file, sparse tokens. No model runs, no sandbox tests. No findings, linting clean. Grade B and 86% quality suggest incomplete docs but working syntax.
Use this if you're streaming data in Vovk.ts and need generator reference. Skip if you expect ready-made examples for your specific framework — check the source repo first.
Vovk.ts JSON Lines streaming — generator handlers (function, async function), the iteration validation option, validateEachIteration, the JSONLinesResponder…
As a process D 49/100 · Unfinished process — weak spots: result and completion, inputs and preconditions, failures and branches
How to improve
- Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
- A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.
Guard findings · 0
✓ No critical or high findings
Files scanned: 1. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
✓ No remarks against the Agent Skills spec
Process rating: all ten parameters 49/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 10 mutating operations with no state check
- 60Tools and files. Uses tools (bash, web) that frontmatter does not declare
- 70When it triggers. States when to use, but not when not to
- 100Steps. 12 steps
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 3079 tokens
Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.
Quality signals
- +4Description does not say when NOT to use the skill (false activations)
- +3Description length 920: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +5Description quotes 11 example trigger phrases
- +4Structure: 21 headings
- +3Step-by-step instructions: 12 items
- +4Has examples (19 code blocks)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 86.