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stream-chain

Chain streaming workflows with deterministic routing, backpressure controls, and evidence-backed checkpoints.

allowed_tools: Read, Write, Edit, Bash, Glob, Grep, Task, TodoWrite
model: sonnet

$ Installer

git clone https://github.com/DNYoussef/context-cascade /tmp/context-cascade && cp -r /tmp/context-cascade/skills/orchestration/stream-chain ~/.claude/skills/context-cascade

// tip: Run this command in your terminal to install the skill


name: stream-chain description: Chain streaming workflows with deterministic routing, backpressure controls, and evidence-backed checkpoints. allowed-tools: Read, Write, Edit, Bash, Glob, Grep, Task, TodoWrite model: sonnet x-version: 3.2.0 x-category: orchestration x-vcl-compliance: v3.2.0 x-cognitive-frames:

  • HON
  • MOR
  • COM
  • CLS
  • EVD
  • ASP
  • SPC

STANDARD OPERATING PROCEDURE

Purpose

Design and operate stream-first chains where partial outputs are consumed live, errors are contained, and confidence ceilings stay explicit.

Trigger Conditions

  • Positive: streaming pipelines, incremental emission, backpressure handling, live fan-out/fan-in, partial-result validation.
  • Negative: batch-only flows, prompt-only edits (route to prompt-architect), or new skill weaving (route to skill-forge).

Guardrails

  • Skill-Forge structure-first: ensure SKILL.md, examples/, tests/ exist; add resources//references/ or document remediation.
  • Prompt-Architect hygiene: capture HARD/SOFT/INFERRED constraints (latency, chunk size, ordering), keep English-only outputs, and declare ceilings.
  • Streaming safety: define buffering, ordering, and retry semantics; enforce registry use; keep hook latency budgets.
  • Adversarial validation: simulate slow consumers, dropped chunks, and ordering skew; capture evidence.
  • MCP tagging: store run logs with WHO=stream-chain-{session} and WHY=skill-execution.

Execution Playbook

  1. Intent & constraints: set latency/SLOs, chunk policy, and delivery guarantees; confirm inferred constraints.
  2. Chain design: map stages, owners, and routing; define backpressure and retry rules.
  3. Implementation: configure streaming hooks, health checks, and telemetry.
  4. Safety nets: set circuit breakers, buffering thresholds, and rollback/compensation steps.
  5. Validation loop: run adversarial drills for slow/failing nodes, check ordering, and log metrics.
  6. Delivery: summarize design, evidence, risks, and confidence ceiling.

Output Format

  • Pipeline overview with constraints and routing.
  • Backpressure/buffering policy and retry/rollback rules.
  • Validation evidence (ordering, loss, latency) and risks.
  • Confidence: X.XX (ceiling: TYPE Y.YY) - rationale.

Validation Checklist

  • Structure-first assets present or ticketed; examples/tests updated for streaming cases.
  • Ordering, retry, and rollback behaviors defined; registry and hooks validated.
  • Adversarial/COV runs captured with MCP tags; confidence ceiling stated; English-only output.

Completion Definition

Stream chain is complete when live runs meet SLOs, failure modes are contained, evidence is stored, and risks are owned with follow-ups.

Confidence: 0.70 (ceiling: inference 0.70) - Stream-chain documentation aligned to skill-forge scaffolding and prompt-architect evidence/confidence rules.