[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6H923G4APK9A3F5VR7FM2CS":3,"skill-same:01M6H923G4APK9A3F5VR7FM2CS":69},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":15,"categories":16,"keywords":17,"publishedAt":38,"linkOnly":39,"markdownContent":40,"markdownBody":41,"frontMatter":42,"refName":48,"commitSha":49,"skillDirectory":50,"forksCount":51,"repositoryHtmlUrl":52,"repositoryHomepageUrl":6,"ownerHtmlUrl":53,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":54,"install":55,"resources":68},"01M6H923G4APK9A3F5VR7FM2CS","speak-sdk-patterns",null,"Apply production-ready Speak SDK patterns for TypeScript and Python.\nUse when implementing Speak integrations, refactoring SDK usage,\nor establishing team coding standards for language learning features.\nTrigger with phrases like \"speak SDK patterns\", \"speak best practices\",\n\"speak code patterns\", \"idiomatic speak\".","micsapp\u002Fmicstec-skills","micsapp","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F82411001?v=4","01M6GWCFQ6D3PV8EHNY62NN5VW","01M6GWCFVE1PA5HG0DKC7AMFJ3",4,"MIT","https:\u002F\u002Fgithub.com\u002Fmicsapp\u002Fmicstec-skills\u002Fblob\u002Fmaster\u002Fclaude-code\u002Fplugins-plus-skills\u002Fplugins\u002Fsaas-packs\u002Fspeak-pack\u002Fskills\u002Fspeak-sdk-patterns\u002FSKILL.md",[],[18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37],"sdk","speak sdk patterns","patterns","speak","write","implementing","production-ready","code patterns","io","language learning","ready","edit","openclaw","read","coding","refactoring","team","coding standards","code","typescript","2026-11-10 10:12:30",false,"---\nname: speak-sdk-patterns\ndescription: |\n  Apply production-ready Speak SDK patterns for TypeScript and Python.\n  Use when implementing Speak integrations, refactoring SDK usage,\n  or establishing team coding standards for language learning features.\n  Trigger with phrases like \"speak SDK patterns\", \"speak best practices\",\n  \"speak code patterns\", \"idiomatic speak\".\nallowed-tools: Read, Write, Edit\nversion: 1.0.0\nlicense: MIT\nauthor: Jeremy Longshore \u003Cjeremy@intentsolutions.io>\ncompatible-with: claude-code, codex, openclaw\n---\n# Speak SDK Patterns\n\n## Overview\nProduction patterns for Speak's language learning REST API. Speak provides pronunciation assessment, conversation practice, and language proficiency evaluation through audio analysis endpoints.\n\n## Prerequisites\n- Speak API key configured\n- Audio recording capability (WAV\u002FMP3 format)\n- Understanding of language learning assessment concepts\n\n## Instructions\n\n### Step 1: Client Setup with Audio Handling\n\n```python\nimport requests\nimport os\n\nclass SpeakClient:\n    def __init__(self, api_key: str = None):\n        self.api_key = api_key or os.environ[\"SPEAK_API_KEY\"]\n        self.base_url = \"https:\u002F\u002Fapi.speak.com\u002Fv1\"\n        self.session = requests.Session()\n        self.session.headers[\"Authorization\"] = f\"Bearer {self.api_key}\"\n\n    def _post(self, path: str, **kwargs):\n        r = self.session.post(f\"{self.base_url}{path}\", **kwargs)\n        r.raise_for_status()\n        return r.json()\n```\n\n### Step 2: Pronunciation Assessment\n\n```python\n    def assess_pronunciation(self, audio_path: str, target_text: str, language: str = \"en\") -> dict:\n        with open(audio_path, 'rb') as f:\n            return self._post(\"\u002Fpronunciation\u002Fassess\", files={\n                \"audio\": (os.path.basename(audio_path), f, \"audio\u002Fwav\")\n            }, data={\n                \"text\": target_text,\n                \"language\": language,\n                \"detail_level\": \"phoneme\"  # word, sentence, or phoneme\n            })\n\n# Usage\nclient = SpeakClient()\nresult = client.assess_pronunciation(\"recording.wav\", \"Hello, how are you?\")\nprint(f\"Overall score: {result['score']}\u002F100\")\nfor word in result.get(\"words\", []):\n    print(f\"  {word['text']}: {word['score']}\u002F100\")\n```\n\n### Step 3: Conversation Practice Session\n\n```python\n    def start_conversation(self, scenario: str, language: str = \"en\", level: str = \"intermediate\") -> dict:\n        return self._post(\"\u002Fconversation\u002Fstart\", json={\n            \"scenario\": scenario,\n            \"language\": language,\n            \"proficiency_level\": level\n        })\n\n    def send_turn(self, session_id: str, audio_path: str) -> dict:\n        with open(audio_path, 'rb') as f:\n            return self._post(f\"\u002Fconversation\u002F{session_id}\u002Fturn\", files={\n                \"audio\": (os.path.basename(audio_path), f, \"audio\u002Fwav\")\n            })\n```\n\n### Step 4: Batch Assessment with Rate Limiting\n\n```python\nimport time\n\ndef batch_assess(client: SpeakClient, recordings: list[dict], delay: float = 1.0):\n    results = []\n    for rec in recordings:\n        try:\n            result = client.assess_pronunciation(rec[\"audio\"], rec[\"text\"], rec.get(\"lang\", \"en\"))\n            results.append({\"file\": rec[\"audio\"], \"score\": result[\"score\"]})\n        except requests.HTTPError as e:\n            if e.response.status_code == 429:  # HTTP 429 Too Many Requests\n                time.sleep(float(e.response.headers.get(\"Retry-After\", 10)))\n                result = client.assess_pronunciation(rec[\"audio\"], rec[\"text\"])\n                results.append({\"file\": rec[\"audio\"], \"score\": result[\"score\"]})\n            else:\n                results.append({\"file\": rec[\"audio\"], \"error\": str(e)})\n        time.sleep(delay)\n    return results\n```\n\n## Error Handling\n| Error | Cause | Solution |\n|-------|-------|----------|\n| `400 Bad audio format` | Unsupported codec | Convert to WAV 16kHz mono |\n| `413 Payload too large` | Audio file > 25MB | Trim or compress audio |\n| `429 Rate limited` | Too many assessments | Add delay between requests |\n| Low confidence score | Background noise | Record in quiet environment |\n\n## Examples\n\n### Audio Preprocessing\n```python\nimport subprocess\ndef convert_to_wav(input_path: str, output_path: str):\n    subprocess.run([\n        \"ffmpeg\", \"-i\", input_path, \"-ar\", \"16000\",  # 16000 = configured value\n        \"-ac\", \"1\", \"-f\", \"wav\", output_path\n    ], check=True)\n```\n\n## Resources\n- [Speak API Docs](https:\u002F\u002Fdocs.speak.com)\n\n## Output\n\n- Configuration files or code changes applied to the project\n- Validation report confirming correct implementation\n- Summary of changes made and their rationale","# Speak SDK Patterns\n\n## Overview\nProduction patterns for Speak's language learning REST API. Speak provides pronunciation assessment, conversation practice, and language proficiency evaluation through audio analysis endpoints.\n\n## Prerequisites\n- Speak API key configured\n- Audio recording capability (WAV\u002FMP3 format)\n- Understanding of language learning assessment concepts\n\n## Instructions\n\n### Step 1: Client Setup with Audio Handling\n\n```python\nimport requests\nimport os\n\nclass SpeakClient:\n    def __init__(self, api_key: str = None):\n        self.api_key = api_key or os.environ[\"SPEAK_API_KEY\"]\n        self.base_url = \"https:\u002F\u002Fapi.speak.com\u002Fv1\"\n        self.session = requests.Session()\n        self.session.headers[\"Authorization\"] = f\"Bearer {self.api_key}\"\n\n    def _post(self, path: str, **kwargs):\n        r = self.session.post(f\"{self.base_url}{path}\", **kwargs)\n        r.raise_for_status()\n        return r.json()\n```\n\n### Step 2: Pronunciation Assessment\n\n```python\n    def assess_pronunciation(self, audio_path: str, target_text: str, language: str = \"en\") -> dict:\n        with open(audio_path, 'rb') as f:\n            return self._post(\"\u002Fpronunciation\u002Fassess\", files={\n                \"audio\": (os.path.basename(audio_path), f, \"audio\u002Fwav\")\n            }, data={\n                \"text\": target_text,\n                \"language\": language,\n                \"detail_level\": \"phoneme\"  # word, sentence, or phoneme\n            })\n\n# Usage\nclient = SpeakClient()\nresult = client.assess_pronunciation(\"recording.wav\", \"Hello, how are you?\")\nprint(f\"Overall score: {result['score']}\u002F100\")\nfor word in result.get(\"words\", []):\n    print(f\"  {word['text']}: {word['score']}\u002F100\")\n```\n\n### Step 3: Conversation Practice Session\n\n```python\n    def start_conversation(self, scenario: str, language: str = \"en\", level: str = \"intermediate\") -> dict:\n        return self._post(\"\u002Fconversation\u002Fstart\", json={\n            \"scenario\": scenario,\n            \"language\": language,\n            \"proficiency_level\": level\n        })\n\n    def send_turn(self, session_id: str, audio_path: str) -> dict:\n        with open(audio_path, 'rb') as f:\n            return self._post(f\"\u002Fconversation\u002F{session_id}\u002Fturn\", files={\n                \"audio\": (os.path.basename(audio_path), f, \"audio\u002Fwav\")\n            })\n```\n\n### Step 4: Batch Assessment with Rate Limiting\n\n```python\nimport time\n\ndef batch_assess(client: SpeakClient, recordings: list[dict], delay: float = 1.0):\n    results = []\n    for rec in recordings:\n        try:\n            result = client.assess_pronunciation(rec[\"audio\"], rec[\"text\"], rec.get(\"lang\", \"en\"))\n            results.append({\"file\": rec[\"audio\"], \"score\": result[\"score\"]})\n        except requests.HTTPError as e:\n            if e.response.status_code == 429:  # HTTP 429 Too Many Requests\n                time.sleep(float(e.response.headers.get(\"Retry-After\", 10)))\n                result = client.assess_pronunciation(rec[\"audio\"], rec[\"text\"])\n                results.append({\"file\": rec[\"audio\"], \"score\": result[\"score\"]})\n            else:\n                results.append({\"file\": rec[\"audio\"], \"error\": str(e)})\n        time.sleep(delay)\n    return results\n```\n\n## Error Handling\n| Error | Cause | Solution |\n|-------|-------|----------|\n| `400 Bad audio format` | Unsupported codec | Convert to WAV 16kHz mono |\n| `413 Payload too large` | Audio file > 25MB | Trim or compress audio |\n| `429 Rate limited` | Too many assessments | Add delay between requests |\n| Low confidence score | Background noise | Record in quiet environment |\n\n## Examples\n\n### Audio Preprocessing\n```python\nimport subprocess\ndef convert_to_wav(input_path: str, output_path: str):\n    subprocess.run([\n        \"ffmpeg\", \"-i\", input_path, \"-ar\", \"16000\",  # 16000 = configured value\n        \"-ac\", \"1\", \"-f\", \"wav\", output_path\n    ], check=True)\n```\n\n## Resources\n- [Speak API Docs](https:\u002F\u002Fdocs.speak.com)\n\n## Output\n\n- Configuration files or code changes applied to the project\n- Validation report confirming correct implementation\n- Summary of changes made and their rationale",{"name":5,"author":43,"license":14,"version":44,"description":45,"allowed-tools":46,"compatible-with":47},"Jeremy Longshore \u003Cjeremy@intentsolutions.io>","1.0.0","Apply production-ready Speak SDK patterns for TypeScript and Python.\nUse when implementing Speak integrations, refactoring SDK usage,\nor establishing team coding standards for language learning features.\nTrigger with phrases like \"speak SDK patterns\", \"speak best practices\",\n\"speak code patterns\", \"idiomatic speak\".\n","Read, Write, Edit","claude-code, codex, openclaw","master","3f5d983eb4ef375b749adcd6b07ec03bd82ae8a8","claude-code\u002Fplugins-plus-skills\u002Fplugins\u002Fsaas-packs\u002Fspeak-pack\u002Fskills\u002Fspeak-sdk-patterns",0,"https:\u002F\u002Fgithub.com\u002Fmicsapp\u002Fmicstec-skills","https:\u002F\u002Fgithub.com\u002Fmicsapp","2026-03-20 11:24:18",{"source":8,"skillName":5,"commands":56,"prompt":66,"zipAvailable":67},[57,60,63],{"tool":58,"command":59},"npx","npx skills add micsapp\u002Fmicstec-skills --skill speak-sdk-patterns",{"tool":61,"command":62},"bunx","bunx skills add micsapp\u002Fmicstec-skills --skill speak-sdk-patterns",{"tool":64,"command":65},"pnpm","pnpm dlx skills add micsapp\u002Fmicstec-skills --skill speak-sdk-patterns","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fmicsapp\u002Fmicstec-skills\u002Fblob\u002Fmaster\u002Fclaude-code\u002Fplugins-plus-skills\u002Fplugins\u002Fsaas-packs\u002Fspeak-pack\u002Fskills\u002Fspeak-sdk-patterns\u002FSKILL.md",true,[],[70,106,134,153,173,197],{"skillNo":71,"name":72,"nameZh":6,"description":73,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":74,"categories":75,"keywords":86,"publishedAt":38},"01M6HBTJ02FXBFG9NYEHHYAP52","azure-apim-architecture","Analyzes and explains Azure API Management architecture decisions for enterprise API marketplace implementations using VNet Internal mode, Front Door, hybrid authentication, and multi-environment strategies. 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Use when deploying APIM, creating pipelines, or implementing dev→test→prod promotion strategies.","https:\u002F\u002Fgithub.com\u002Fmicsapp\u002Fmicstec-skills\u002Fblob\u002Fmaster\u002Fcopilot-cli\u002Fcopilot-agent-skills\u002F.github\u002Fskills\u002Fapiops-deployment\u002FSKILL.md",[112,113,116,119],{"categoryNo":77,"categoryName":78,"taxonomyType":79,"taxonomyTypeDesc":80},{"categoryNo":114,"categoryName":115,"taxonomyType":79,"taxonomyTypeDesc":80},"01JBSEEDCAT000000000000011","运维与部署",{"categoryNo":117,"categoryName":118,"taxonomyType":79,"taxonomyTypeDesc":80},"01JBSEEDCAT000000000000023","Skill与智能体开发",{"categoryNo":82,"categoryName":83,"taxonomyType":84,"taxonomyTypeDesc":85},[121,122,123,124,88,125,36,126,127,128,129,130,96,34,102,131,132,103,133,23],"deployment","apiops deployment","workflows","azure devops","infrastructure","infrastructure as code","actions","ci","github actions","github-actions","as","guides","CI\u002FCD",{"skillNo":135,"name":136,"nameZh":6,"description":137,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":138,"categories":139,"keywords":141,"publishedAt":38},"01M6HBT2HEA23THNE9E00GYQBE","apim-policy-authoring","Creates production-ready Azure API Management policy XML for authentication (OAuth 2.0, JWT validation, subscription keys), rate limiting, CORS configuration, error handling, and API transformations. 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Use when the user asks to calculate, compute, or evaluate math expressions, or when precise decimal arithmetic is needed to avoid floating-point errors.","https:\u002F\u002Fgithub.com\u002Fmicsapp\u002Fmicstec-skills\u002Fblob\u002Fmaster\u002Fcopilot-cli\u002Fawesome-copilot-agents\u002Fskills\u002Fcalculator\u002FSKILL.md",[],[199,204,205,206,207,208,209,147,210,211],"npm","js","calculate","node","math","user","compute","errors"]