{"id":"69ced620-0f4f-4e85-9472-4e7989245d47","entityType":"agent","slug":"clawhub-unisound-llm-unisound-med-content-generation","name":"unisound-med-content-generation","canonicalUrl":"https://www.xpersona.co/agent/clawhub-unisound-llm-unisound-med-content-generation","canonicalPath":"/agent/clawhub-unisound-llm-unisound-med-content-generation","generatedAt":"2026-10-13T13:25:30.824Z","source":"CLAWHUB","claimStatus":"UNCLAIMED","verificationTier":"NONE","summary":{"evidence":{"source":"editorial-content","verified":true,"confidence":"high","updatedAt":"2026-10-11T22:46:01.010Z","emptyReason":null},"description":"医学科普、文档摘要、术语释义、教学案例与诊疗文书辅助生成。通过 --task 选择类型；仅含 `scripts/run.py`，可独立拷贝部署。 Skill: unisound-med-content-generation Owner: unisound-llm Summary: 医学科普、文档摘要、术语释义、教学案例与诊疗文书辅助生成。通过 --task 选择类型；仅含 scripts/run.py，可独立拷贝部署。 Tags: latest:1.0.2 Version history: v1.0.2 | 2026-07-16T06:19:48.076Z | user - Default model changed from u1-insuremed to u2-med. - Removed file: skill-card.md (no longer included in this version). v1.0.0 | 2026-05-19T09:29:51.328Z | user - Initial release of medical content gener","descriptionLabel":"Technical summary","evidenceSummary":"Capability contract not published. No trust telemetry is available yet. 982 downloads reported by the source. Last updated 10/11/2026.","installCommand":"clawhub skill install s1770nyybxj4gn0vk38n6wr6k584x8ea:unisound-med-content-generation","sourceUrl":"https://clawhub.ai/unisound-llm/unisound-med-content-generation","homepage":"https://clawhub.ai/unisound-llm/skills/unisound-med-content-generation","primaryLinks":[{"label":"View on ClawHub","url":"https://clawhub.ai/unisound-llm/unisound-med-content-generation","kind":"source"},{"label":"Homepage","url":"https://clawhub.ai/unisound-llm/skills/unisound-med-content-generation","kind":"homepage"}],"safetyScore":84,"overallRank":62,"popularityScore":60,"trustScore":null,"claimedByName":null,"isOwner":false,"seoDescription":"医学科普、文档摘要、术语释义、教学案例与诊疗文书辅助生成。通过 --task 选择类型；仅含 `scripts/run.py`，可独立拷贝部署。 Skill: unisound-med-content-generation Owner: unisound-llm Summary: 医学科普、文档摘要、术语释义、教学案例"},"coverage":{"evidence":{"source":"public-profile","verified":false,"confidence":"medium","updatedAt":"2026-10-11T22:46:01.010Z","emptyReason":null},"protocols":[{"protocol":"OPENCLEW","label":"OpenClaw","status":"self-declared","notes":"Declared in the public agent profile."}],"capabilities":[],"verifiedCount":0,"selfDeclaredCount":1,"capabilityMatrix":{"rows":[{"key":"OPENCLEW","type":"protocol","support":"unknown","confidenceSource":"profile","notes":"Listed on profile"}],"flattenedTokens":"protocol:OPENCLEW|unknown|profile"}},"adoption":{"evidence":{"source":"CLAWHUB","verified":false,"confidence":"medium","updatedAt":"2026-10-11T22:46:01.010Z","emptyReason":null},"stars":null,"forks":null,"downloads":982,"likes":null,"task":null,"library":null,"packageName":null,"latestVersion":"1.0.2","tractionLabel":"982 downloads"},"release":{"evidence":{"source":"CLAWHUB","verified":false,"confidence":"medium","updatedAt":"2026-10-11T22:46:00.938Z","emptyReason":null},"lastUpdatedAt":"2026-10-11T22:46:01.010Z","lastCrawledAt":"2026-10-11T22:46:00.938Z","lastIndexedAt":null,"nextCrawlAt":"2026-10-12T22:46:00.938Z","lastVerifiedAt":null,"highlights":[{"version":"1.0.2","createdAt":"2026-07-16T06:19:48.076Z","changelog":"- Default model changed from `u1-insuremed` to `u2-med`. - Removed file: `skill-card.md` (no longer included in this version).","fileCount":4,"zipByteSize":8037},{"version":"1.0.0","createdAt":"2026-05-19T09:29:51.328Z","changelog":"- Initial release of medical content generation and explanation skill. - Supports multiple tasks: medical term explanation, popular science, clinical document drafting, summary generation, and teaching cases (switch via --task). - Flexible input methods: direct question, JSON/JSONL/text file, or stdin. - Outputs answers as structured JSON, suitable for integration and further processing. - Includes dry-run mode for input parsing without invoking the model. - Designed for secure deployment using internal medical LLM with API key authentication.","fileCount":4,"zipByteSize":8132}]},"execution":{"evidence":{"source":"CLAWHUB","verified":false,"confidence":"low","updatedAt":null,"emptyReason":"No published capability contract is available yet."},"installCommand":"clawhub skill install s1770nyybxj4gn0vk38n6wr6k584x8ea:unisound-med-content-generation","setupComplexity":"low","setupSteps":["Setup complexity is LOW. 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unisound-llm\n\nSummary: 医学科普、文档摘要、术语释义、教学案例与诊疗文书辅助生成。通过 --task 选择类型；仅含 `scripts/run.py`，可独立拷贝部署。\n\nTags: latest:1.0.2\n\nVersion history:\n\nv1.0.2 | 2026-07-16T06:19:48.076Z | user\n\n- Default model changed from `u1-insuremed` to `u2-med`.\n- Removed file: `skill-card.md` (no longer included in this version).\n\nv1.0.0 | 2026-05-19T09:29:51.328Z | user\n\n- Initial release of medical content generation and explanation skill.\n- Supports multiple tasks: medical term explanation, popular science, clinical document drafting, summary generation, and teaching cases (switch via --task).\n- Flexible input methods: direct question, JSON/JSONL/text file, or stdin.\n- Outputs answers as structured JSON, suitable for integration and further processing.\n- Includes dry-run mode for input parsing without invoking the model.\n- Designed for secure deployment using internal medical LLM with API key authentication.\n\nArchive index:\n\nArchive v1.0.2: 4 files, 8037 bytes\n\nFiles: _meta.json (150b), scripts/run.py (13329b), skill-card.md (2360b), SKILL.md (3140b)\n\nFile v1.0.2:SKILL.md\n\n---\nname: med-llm-content-generation\ndescription: 医学科普、文档摘要、术语释义、教学案例与诊疗文书辅助生成。通过 --task 选择类型；仅含 `scripts/run.py`，可独立拷贝部署。\nmetadata:\n {\n \"openclaw\":\n {\n \"emoji\": \"🩺\"\n }\n }\n---\n\n# 医学内容生成与解释\n\n## 概述\n\n面向医学内容生产与通俗化解释，输出须符合医学规范且标注为辅助材料。\n\n具体场景通过 **`--task`** 切换系统提示词（见下表），能力依赖内部医疗大模型；集成方也可通过 `--system-prompt` 完全自定义。\n\n| `--task` | 能力 |\n| --- | --- |\n| `explain` | 医学术语通俗释义 |\n| `popular` | 医学科普内容生成 |\n| `record-gen` | 诊疗文书辅助生成 |\n| `summary` | 临床文档摘要生成 |\n| `teach` | 临床教学案例生成 |\n\n本能力与具体业务请求解耦：平台或调用方如何组织用户输入由集成方决定；此处只约定**如何把题目交给脚本**（见下）。\n\n## 题目输入（三选一）\n\n1. **`--question`**：直接传入完整题干字符串。 \n2. **`--input PATH`**： \n - `.jsonl`：每行一个 JSON 对象，须含非空字符串字段 `question`；可用 `--index` / `--batch` / `--match-id` 选取记录； \n - `.json`：单个对象，须含 `question`； \n - 其他扩展名：按 UTF-8 纯文本整文件作为题干。 \n - 传 `-` 时从 **stdin** 读取一条 JSON（含 `question`）或纯文本。 \n3. **stdin**（且未传 `--question` / `--input`、且 stdin 非 TTY）：读入 JSON 对象或纯文本，规则同 `-`。\n\n可在 JSON 的 `other.task` 中指定任务类型（与 `--task` 等价；命令行 `--task` 优先）。\n\n## 模型\n\n- 默认 `u2-med`，接口 `https://maas-api.hivoice.cn/v1/chat/completions`（可通过参数覆盖）。\n\n## 用法示例\n\n```bash\n# 指定任务类型与题干\npython3 scripts/run.py --task explain --question \"题干……\" --appkey YOUR_KEY\n\n# 从 jsonl 取题（other.task 可省略若命令行已传 --task）\npython3 scripts/run.py --task explain --input /path/to/items.jsonl --index 0 --appkey YOUR_KEY\n```\n\n## 参数\n\n- `--task`：**必填**（除非 `other.task` 已给出）。见上表。\n- `--question` / `--input`：见上，与 stdin 三选一（`--question` 与 `--input` 不可同时使用）。\n- `--appkey STRING`：**必填**（`--dry-run` 时除外）。内部医疗大模型鉴权 key。\n- `--index`、`--match-id`、`--batch`：仅对 `.jsonl` 生效。\n- `--dry-run`：不调用模型，仅输出解析后的题目 JSON。\n- `--model`、`--api-url`、`--temperature`、`--timeout`、`--system-prompt`：调模型参数。\n- `--output PATH`：另存完整 JSON（批量为 NDJSON）。\n- `--text-only`：标准输出仅打印模型答案文本。\n\n## 输出\n\n默认可解析 JSON：含 `status`、`task`、`task_title`、`question`、`answer`、`record_index`、`meta`、`model`、`input_mode`、`input_path` 等；`skill` 为本 skill 标题。\n\n## 合规说明\n\n输出为模型辅助信息，不构成正式诊疗决策；涉及真实患者数据须先脱敏并遵守院内流程。\n\nFile v1.0.2:_meta.json\n\n{\n \"ownerId\": \"kn7ft98qwhxyrgcy7b7rzdhrrd8366k6\",\n \"slug\": \"unisound-med-content-generation\",\n \"version\": \"1.0.2\",\n \"publishedAt\": 1784182788076\n}\n\nFile v1.0.2:skill-card.md\n\n## Description:\n\nGenerates medical education content, clinical-document summaries, terminology explanations, teaching cases, and draft clinical note text through selectable task modes.\n\nThis skill is ready for commercial/non-commercial use.\n\n## Publisher:\n\n[unisound-llm](https://clawhub.ai/user/unisound-llm)\n\n### License/Terms of Use:\n\nMIT-0\n\n## Use Case:\n\nHealthcare content teams, educators, and integrators use this skill to turn a supplied medical question or document excerpt into auxiliary explanatory, educational, summarization, or draft documentation output. Use only de-identified medical content and human review because outputs are not clinical decisions.\n\n### Deployment Geography for Use:\n\nGlobal\n\n## Known Risks and Mitigations:\n\nRisk: Sensitive medical text may be sent to a configurable remote API.\n\nMitigation: Use only de-identified medical content and verify that the configured endpoint is a trusted HTTPS service approved for the workflow.\n\nRisk: Bearer app keys may be exposed to untrusted custom endpoints or command-line handling.\n\nMitigation: Treat app keys as sensitive, avoid production keys with custom endpoints, and keep keys out of logs, shell history, and shared scripts.\n\nRisk: Generated medical content may be inaccurate or unsuitable for clinical use.\n\nMitigation: Require qualified human review and follow institutional procedures before using outputs in education, documentation, or patient-facing material.\n\n## Reference(s):\n\n- [ClawHub skill page](https://clawhub.ai/unisound-llm/skills/unisound-med-content-generation)\n- [Publisher profile](https://clawhub.ai/user/unisound-llm)\n- [Default API endpoint](https://maas-api.hivoice.cn/v1/chat/completions)\n\n## Skill Output:\n\n**Output Type(s):** [text, JSON, files]\n\n**Output Format:** [JSON by default, plain text with --text-only, and NDJSON for batch output]\n\n**Output Parameters:** [1D]\n\n**Other Properties Related to Output:** [Can save full JSON or NDJSON to --output; dry-run returns parsed input without calling the model.]\n\n## Skill Version(s):\n\n1.0.2 (source: server-resolved release metadata)\n\n## Ethical Considerations:\n\nUsers should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment.\n\nArchive v1.0.0: 4 files, 8132 bytes\n\nFiles: _meta.json (150b), scripts/run.py (13335b), skill-card.md (2356b), SKILL.md (3146b)\n\nFile v1.0.0:SKILL.md\n\n---\nname: med-llm-content-generation\ndescription: 医学科普、文档摘要、术语释义、教学案例与诊疗文书辅助生成。通过 --task 选择类型；仅含 `scripts/run.py`，可独立拷贝部署。\nmetadata:\n {\n \"openclaw\":\n {\n \"emoji\": \"🩺\"\n }\n }\n---\n\n# 医学内容生成与解释\n\n## 概述\n\n面向医学内容生产与通俗化解释，输出须符合医学规范且标注为辅助材料。\n\n具体场景通过 **`--task`** 切换系统提示词（见下表），能力依赖内部医疗大模型；集成方也可通过 `--system-prompt` 完全自定义。\n\n| `--task` | 能力 |\n| --- | --- |\n| `explain` | 医学术语通俗释义 |\n| `popular` | 医学科普内容生成 |\n| `record-gen` | 诊疗文书辅助生成 |\n| `summary` | 临床文档摘要生成 |\n| `teach` | 临床教学案例生成 |\n\n本能力与具体业务请求解耦：平台或调用方如何组织用户输入由集成方决定；此处只约定**如何把题目交给脚本**（见下）。\n\n## 题目输入（三选一）\n\n1. **`--question`**：直接传入完整题干字符串。 \n2. **`--input PATH`**： \n - `.jsonl`：每行一个 JSON 对象，须含非空字符串字段 `question`；可用 `--index` / `--batch` / `--match-id` 选取记录； \n - `.json`：单个对象，须含 `question`； \n - 其他扩展名：按 UTF-8 纯文本整文件作为题干。 \n - 传 `-` 时从 **stdin** 读取一条 JSON（含 `question`）或纯文本。 \n3. **stdin**（且未传 `--question` / `--input`、且 stdin 非 TTY）：读入 JSON 对象或纯文本，规则同 `-`。\n\n可在 JSON 的 `other.task` 中指定任务类型（与 `--task` 等价；命令行 `--task` 优先）。\n\n## 模型\n\n- 默认 `u1-insuremed`，接口 `https://maas-api.hivoice.cn/v1/chat/completions`（可通过参数覆盖）。\n\n## 用法示例\n\n```bash\n# 指定任务类型与题干\npython3 scripts/run.py --task explain --question \"题干……\" --appkey YOUR_KEY\n\n# 从 jsonl 取题（other.task 可省略若命令行已传 --task）\npython3 scripts/run.py --task explain --input /path/to/items.jsonl --index 0 --appkey YOUR_KEY\n```\n\n## 参数\n\n- `--task`：**必填**（除非 `other.task` 已给出）。见上表。\n- `--question` / `--input`：见上，与 stdin 三选一（`--question` 与 `--input` 不可同时使用）。\n- `--appkey STRING`：**必填**（`--dry-run` 时除外）。内部医疗大模型鉴权 key。\n- `--index`、`--match-id`、`--batch`：仅对 `.jsonl` 生效。\n- `--dry-run`：不调用模型，仅输出解析后的题目 JSON。\n- `--model`、`--api-url`、`--temperature`、`--timeout`、`--system-prompt`：调模型参数。\n- `--output PATH`：另存完整 JSON（批量为 NDJSON）。\n- `--text-only`：标准输出仅打印模型答案文本。\n\n## 输出\n\n默认可解析 JSON：含 `status`、`task`、`task_title`、`question`、`answer`、`record_index`、`meta`、`model`、`input_mode`、`input_path` 等；`skill` 为本 skill 标题。\n\n## 合规说明\n\n输出为模型辅助信息，不构成正式诊疗决策；涉及真实患者数据须先脱敏并遵守院内流程。\n\nFile v1.0.0:_meta.json\n\n{\n \"ownerId\": \"kn7ft98qwhxyrgcy7b7rzdhrrd8366k6\",\n \"slug\": \"unisound-med-content-generation\",\n \"version\": \"1.0.0\",\n \"publishedAt\": 1779182991328\n}\n\nFile v1.0.0:skill-card.md\n\n## Description:
\n医学科普、文档摘要、术语释义、教学案例与诊疗文书辅助生成。通过 --task 选择类型；仅含 `scripts/run.py`，可独立拷贝部署。
\n\nThis skill is ready for commercial/non-commercial use.
\n\n## Publisher:
\n[unisound-llm](https://clawhub.ai/user/unisound-llm)
\n\n### License/Terms of Use:
\nMIT-0
\n\n\n## Use Case:
\nExternal developers and medical content teams use this skill to send medical questions or source documents to a configured medical LLM for plain-language explanations, popular science content, clinical summaries, teaching cases, and draft clinical documentation. Outputs are auxiliary material and are not a substitute for clinical judgment.
\n\n### Deployment Geography for Use:
\nGlobal
\n\n## Known Risks and Mitigations:
\nRisk: Medical prompts and source documents are sent to the configured medical LLM API.
\nMitigation: Use only approved endpoints and keys, and submit patient information only after de-identification and organizational approval.
\nRisk: Generated medical explanations, summaries, teaching cases, or draft documentation may be incomplete or clinically incorrect.
\nMitigation: Treat outputs as auxiliary material and require qualified clinical review before use in care, documentation, or patient-facing communication.
\n\n\n## Reference(s):
\n- [ClawHub skill page](https://clawhub.ai/unisound-llm/unisound-med-content-generation)
\n- [ClawHub publisher profile](https://clawhub.ai/user/unisound-llm)
\n\n\n## Skill Output:
\n**Output Type(s):** [Text, JSON, Markdown, Shell commands, Configuration]
\n**Output Format:** [JSON by default, text-only answer output when requested, and NDJSON for batch results]
\n**Output Parameters:** [1D]
\n**Other Properties Related to Output:** [Supports task selection, JSON/JSONL/text/stdin inputs, dry-run parsing, output files, and configurable API URL, model, temperature, timeout, and system prompt.]
\n\n## Skill Version(s):
\n1.0.0 (source: server release metadata)
\n\n## Ethical Considerations:
\nUsers should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment.
","readmeExcerpt":"Skill: unisound-med-content-generation Owner: unisound-llm Summary: 医学科普、文档摘要、术语释义、教学案例与诊疗文书辅助生成。通过 --task 选择类型；仅含 scripts/run.py，可独立拷贝部署。 Tags: latest:1.0.2 Version history: v1.0.2 | 2026-07-16T06:19:48.076Z | user - Default model changed from u1-insuremed to u2-med. - Removed file: skill-card.md (no longer included in this version). v1.0.0 | 2026-05-19T09:29:51.328Z | user - Initial release of medical content gener","codeSnippets":[],"executableExamples":[{"language":"bash","snippet":"# 指定任务类型与题干\npython3 scripts/run.py --task explain --question \"题干……\" --appkey YOUR_KEY\n\n# 从 jsonl 取题（other.task 可省略若命令行已传 --task）\npython3 scripts/run.py --task explain --input /path/to/items.jsonl --index 0 --appkey YOUR_KEY"},{"language":"bash","snippet":"# 指定任务类型与题干\npython3 scripts/run.py --task explain --question \"题干……\" --appkey YOUR_KEY\n\n# 从 jsonl 取题（other.task 可省略若命令行已传 --task）\npython3 scripts/run.py --task explain --input /path/to/items.jsonl --index 0 --appkey YOUR_KEY"}],"parameters":null,"dependencies":[],"permissions":[],"extractedFiles":[{"path":"SKILL.md","content":"---\nname: med-llm-content-generation\ndescription: 医学科普、文档摘要、术语释义、教学案例与诊疗文书辅助生成。通过 --task 选择类型；仅含 `scripts/run.py`，可独立拷贝部署。\nmetadata:\n {\n \"openclaw\":\n {\n \"emoji\": \"🩺\"\n }\n }\n---\n\n# 医学内容生成与解释\n\n## 概述\n\n面向医学内容生产与通俗化解释，输出须符合医学规范且标注为辅助材料。\n\n具体场景通过 **`--task`** 切换系统提示词（见下表），能力依赖内部医疗大模型；集成方也可通过 `--system-prompt` 完全自定义。\n\n| `--task` | 能力 |\n| --- | --- |\n| `explain` | 医学术语通俗释义 |\n| `popular` | 医学科普内容生成 |\n| `record-gen` | 诊疗文书辅助生成 |\n| `summary` | 临床文档摘要生成 |\n| `teach` | 临床教学案例生成 |\n\n本能力与具体业务请求解耦：平台或调用方如何组织用户输入由集成方决定；此处只约定**如何把题目交给脚本**（见下）。\n\n## 题目输入（三选一）\n\n1. **`--question`**：直接传入完整题干字符串。 \n2. **`--input PATH`**： \n - `.jsonl`：每行一个 JSON 对象，须含非空字符串字段 `question`；可用 `--index` / `--batch` / `--match-id` 选取记录； \n - `.json`：单个对象，须含 `question`； \n - 其他扩展名：按 UTF-8 纯文本整文件作为题干。 \n - 传 `-` 时从 **stdin** 读取一条 JSON（含 `question`）或纯文本。 \n3. **stdin**（且未传 `--question` / `--input`、且 stdin 非 TTY）：读入 JSON 对象或纯文本，规则同 `-`。\n\n可在 JSON 的 `other.task` 中指定任务类型（与 `--task` 等价；命令行 `--task` 优先）。\n\n## 模型\n\n- 默认 `u2-med`，接口 `https://maas-api.hivoice.cn/v1/chat/completions`（可通过参数覆盖）。\n\n## 用法示例\n\n```bash\n# 指定任务类型与题干\npython3 scripts/run.py --task explain --question \"题干……\" --appkey YOUR_KEY\n\n# 从 jsonl 取题（other.task 可省略若命令行已传 --task）\npython3 scripts/run.py --task explain --input /path/to/items.jsonl --index 0 --appkey YOUR_KEY\n```\n\n## 参数\n\n- `--task`：**必填**（除非 `other.task` 已给出）。见上表。\n- `--question` / `--input`：见上，与 stdin 三选一（`--question` 与 `--input` 不可同时使用）。\n- `--appkey STRING`：**必填**（`--dry-run` 时除外）。内部医疗大模型鉴权 key。\n- `--index`、`--match-id`、`--batch`：仅对 `.jsonl` 生效。\n- `--dry-run`：不调用模型，仅输出解析后的题目 JSON。\n- `--model`、`--api-url`、`--temperature`、`--timeout`、`--system-prompt`：调模型参数。\n- `--output PATH`：另存完整 JSON（批量为 NDJSON）。\n- `--text-only`：标准输出仅打印模型答案文本。\n\n## 输出\n\n默认可解析 JSON：含 `status`、`task`、`task_title`、`question`、`answer`、`record_index`、`meta`、`model`、`input_mode`、`input_path` 等；`skill` 为本 skill 标题。\n\n## 合规说明\n\n输出为模型辅助信息，不构成正式诊疗决策；涉及真实患者数据须先脱敏并遵守院内流程。"},{"path":"_meta.json","content":"{\n \"ownerId\": \"kn7ft98qwhxyrgcy7b7rzdhrrd8366k6\",\n \"slug\": \"unisound-med-content-generation\",\n \"version\": \"1.0.2\",\n \"publishedAt\": 1784182788076\n}"},{"path":"skill-card.md","content":"## Description:\n\nGenerates medical education content, clinical-document summaries, terminology explanations, teaching cases, and draft clinical note text through selectable task modes.\n\nThis skill is ready for commercial/non-commercial use.\n\n## Publisher:\n\n[unisound-llm](https://clawhub.ai/user/unisound-llm)\n\n### License/Terms of Use:\n\nMIT-0\n\n## Use Case:\n\nHealthcare content teams, educators, and integrators use this skill to turn a supplied medical question or document excerpt into auxiliary explanatory, educational, summarization, or draft documentation output. Use only de-identified medical content and human review because outputs are not clinical decisions.\n\n### Deployment Geography for Use:\n\nGlobal\n\n## Known Risks and Mitigations:\n\nRisk: Sensitive medical text may be sent to a configurable remote API.\n\nMitigation: Use only de-identified medical content and verify that the configured endpoint is a trusted HTTPS service approved for the workflow.\n\nRisk: Bearer app keys may be exposed to untrusted custom endpoints or command-line handling.\n\nMitigation: Treat app keys as sensitive, avoid production keys with custom endpoints, and keep keys out of logs, shell history, and shared scripts.\n\nRisk: Generated medical content may be inaccurate or unsuitable for clinical use.\n\nMitigation: Require qualified human review and follow institutional procedures before using outputs in education, documentation, or patient-facing material.\n\n## Reference(s):\n\n- [ClawHub skill page](https://clawhub.ai/unisound-llm/skills/unisound-med-content-generation)\n- [Publisher profile](https://clawhub.ai/user/unisound-llm)\n- [Default API endpoint](https://maas-api.hivoice.cn/v1/chat/completions)\n\n## Skill Output:\n\n**Output Type(s):** [text, JSON, files]\n\n**Output Format:** [JSON by default, plain text with --text-only, and NDJSON for batch output]\n\n**Output Parameters:** [1D]\n\n**Other Properties Related to Output:** [Can save full JSON or NDJSON to --output; dry-run returns parsed input without calling the model.]\n\n## Skill Version(s):\n\n1.0.2 (source: server-resolved release metadata)\n\n## Ethical Considerations:\n\nUsers should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment."}],"languages":[],"docsSourceLabel":"CLAWHUB","editorialOverview":"医学科普、文档摘要、术语释义、教学案例与诊疗文书辅助生成。通过 --task 选择类型；仅含 `scripts/run.py`，可独立拷贝部署。 Skill: unisound-med-content-generation Owner: unisound-llm Summary: 医学科普、文档摘要、术语释义、教学案例与诊疗文书辅助生成。通过 --task 选择类型；仅含 scripts/run.py，可独立拷贝部署。 Tags: latest:1.0.2 Version history: v1.0.2 | 2026-07-16T06:19:48.076Z | user - Default model changed from u1-insuremed to u2-med. - Removed file: skill-card.md (no longer included in this version). v1.0.0 | 2026-05-19T09:29:51.328Z | user - Initial release of medical content gener","editorialQuality":{"score":100,"threshold":65,"status":"ready","wordCount":891,"uniquenessScore":56,"reasons":[]}},"media":{"evidence":{"source":"no-media","verified":false,"confidence":"low","updatedAt":"2026-10-11T22:46:01.010Z","emptyReason":"No screenshots, media assets, or demo links are available."},"primaryImageUrl":null,"mediaAssetCount":0,"assets":[],"demoUrl":null},"ownerResources":{"evidence":{"source":"unclaimed","verified":false,"confidence":"low","updatedAt":"2026-10-11T22:46:01.010Z","emptyReason":"This page has not been claimed by the agent owner."},"hasCustomPage":false,"customPageUpdatedAt":null,"customLinks":[],"structuredLinks":{"docsUrl":null,"demoUrl":null,"supportUrl":null,"pricingUrl":null,"statusUrl":null},"customPage":null},"relatedAgents":{"evidence":{"source":"protocol-neighbors","verified":false,"confidence":"medium","updatedAt":"2026-10-13T13:25:30.824Z","emptyReason":null},"items":[{"id":"8ebccd8e-3863-4187-8355-c3f14e1f9edf","entityType":"agent","canonicalPath":"/agent/iofficeai-aionui","slug":"iofficeai-aionui","name":"AionUi","description":"Free, local, open-source 24/7 Cowork app and OpenClaw for Gemini CLI, Claude Code, Codex, OpenCode, Qwen Code, Goose CLI, Auggie, and more | 🌟 Star if you like it!","url":"https://github.com/iOfficeAI/AionUi","homepage":"https://www.aionui.com","source":"GITHUB_REPOS","protocols":["MCP","OPENCLAW"],"capabilities":[],"safetyScore":100,"overallRank":70,"updatedAt":"2026-10-09T19:11:12.944Z","createdAt":"2026-02-25T03:38:16.584Z","downloads":null},{"id":"b917f68a-ebff-438e-84f8-3f4b2494c0bc","entityType":"agent","canonicalPath":"/agent/activepieces-activepieces","slug":"activepieces-activepieces","name":"activepieces","description":"AI Agents & MCPs & AI Workflow Automation • (~400 MCP servers for AI agents) • AI Automation / AI Agent with MCPs • AI Workflows & AI Agents • MCPs for AI Agents","url":"https://github.com/activepieces/activepieces","homepage":"https://www.activepieces.com","source":"GITHUB_REPOS","protocols":["OPENCLAW"],"capabilities":[],"safetyScore":100,"overallRank":70,"updatedAt":"2026-04-15T02:22:12.426Z","createdAt":"2026-02-25T03:38:12.412Z","downloads":null},{"id":"5cb26759-3a39-483f-94cf-276a98c13bb8","entityType":"agent","canonicalPath":"/agent/cherryhq-cherry-studio","slug":"cherryhq-cherry-studio","name":"cherry-studio","description":"AI productivity studio with smart chat, autonomous agents, and 300+ assistants. 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