From claude-commands
Define evidence requirements for end-to-end streaming chunk delivery from LLM to HTTP SSE, including timestamps, joined tables, and pass/fail thresholds.
How this skill is triggered — by the user, by Claude, or both
Slash command
/claude-commands:streaming-evidence-standardsThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
**Purpose**: Prove end-to-end streaming chunk delivery from LLM output to HTTP SSE client with timestamped, sequence-level evidence.
Purpose: Prove end-to-end streaming chunk delivery from LLM output to HTTP SSE client with timestamped, sequence-level evidence.
BD-iwrroadmap/2026-02-11-streaming-evidence-reference-standard.mdLLM-to-HTTP Chunk Timing Evidence Requirementcampaign_idrequest_id (or stable equivalent)sequencellm_ts_utchttp_ts_utcdelta_ms = http_ts - llm_tsp50/p95/max of delta_msp95(delta_ms) <= 2000 msmax(delta_ms) <= 5000 mscampaign_id/request_id appears across all artifacts.Mark FAIL when any apply:
npx claudepluginhub jleechanorg/claude-commands --plugin claude-commandsImplements OpenRouter streaming with OpenAI SDK in Python and TypeScript for real-time chat UIs via SSE, reducing TTFT and capturing usage metrics.
Optimizes end-to-end latency in distributed systems with budgets, geographic routing, protocol tweaks, and measurement techniques for user-facing apps.
Validates deliverables and builds evidence trails for multi-agent handoffs, with fidelity checks for compressed outputs and structured disagreement reporting.