From speak-pack
Provides production readiness checklist for Speak language learning API integrations: auth, audio pipeline with ffmpeg, rate limiting, monitoring, compliance. For prod setups and troubleshooting.
npx claudepluginhub jeremylongshore/claude-code-plugins-plus-skills --plugin speak-packThis skill is limited to using the following tools:
Production readiness checklist for Speak language learning integrations: auth, audio pipeline, monitoring, and compliance.
Provides TypeScript patterns for Speak language learning API: conversation sessions, pronunciation assessment, ffmpeg audio preprocessing, retries. For SDK integration or troubleshooting.
Guides Next.js Cache Components and Partial Prerendering (PPR): 'use cache' directives, cacheLife(), cacheTag(), revalidateTag() for caching, invalidation, static/dynamic optimization. Auto-activates on cacheComponents: true.
Guides building MCP servers enabling LLMs to interact with external services via tools. Covers best practices, TypeScript/Node (MCP SDK), Python (FastMCP).
Share bugs, ideas, or general feedback.
Production readiness checklist for Speak language learning integrations: auth, audio pipeline, monitoring, and compliance.
speak-install-auth setup#!/bin/bash
set -euo pipefail
echo "Speak Production Readiness"
curl -sf -H "Authorization: Bearer $SPEAK_API_KEY" \
https://api.speak.com/v1/health | jq '.status'
echo " Auth: PASS"
ffmpeg -version > /dev/null 2>&1 && echo " ffmpeg: PASS" || echo " ffmpeg: FAIL"
echo "Checks complete."
| Error | Cause | Solution |
|---|---|---|
| 401 Unauthorized | Invalid API key | Verify SPEAK_API_KEY environment variable |
| 429 Rate Limited | Too many requests | Wait Retry-After seconds, use backoff |
| Audio format error | Wrong codec/sample rate | Convert to WAV 16kHz mono with ffmpeg |
| Session expired | Timeout after 30 min | Start a new conversation session |
See speak-prod-checklist for production readiness.
Basic: Apply prod checklist with default configuration for a standard Speak integration.
Advanced: Customize for production with error recovery, monitoring, and team-specific requirements.