Routines
google/adk-recipes
A skill your agent uses for a recurring unattended task (cron; pull data, open a PR, post a digest), or to test/dry-run a routine first.
当用户需要对常规体检报告进行专业、结构化的解析，提取异常指标、异常结论、边界值异常、复查建议、长期健康风险线索和与核保相关的重要医学信息，并生成适合保险核保、补问流转和资料审查的结构化解析结果时使用本 skill。
Apache-2.0Auto-check passed
Install Routine Physical Exam Report Analysis Assistant
$ npx skills add aifinlab/FinClaw --skill routine-physical-exam-report-analysis-assistant -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install aifinlab/FinClaw routine-physical-exam-report-analysis-assistant --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/aifinlab/FinClaw.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/routine-physical-exam-report-analysis-assistant .claude/skills/routine-physical-exam-report-analysis-assistant && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "routine-physical-exam-report-analysis-assistant" agent skill from https://github.com/aifinlab/FinClaw/tree/main/skills/routine-physical-exam-report-analysis-assistant into .claude/skills/routine-physical-exam-report-analysis-assistant/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "routine-physical-exam-report-analysis-assistant", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/aifinlab/FinClaw/tree/main/skills/routine-physical-exam-report-analysis-assistantType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add aifinlab/FinClaw --skill routine-physical-exam-report-analysis-assistant -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install aifinlab/FinClaw routine-physical-exam-report-analysis-assistant --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aifinlab/FinClaw.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/routine-physical-exam-report-analysis-assistant .agents/skills/routine-physical-exam-report-analysis-assistant && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "routine-physical-exam-report-analysis-assistant" agent skill from https://github.com/aifinlab/FinClaw/tree/main/skills/routine-physical-exam-report-analysis-assistant into .agents/skills/routine-physical-exam-report-analysis-assistant/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "routine-physical-exam-report-analysis-assistant", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add aifinlab/FinClaw --skill routine-physical-exam-report-analysis-assistant -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install aifinlab/FinClaw routine-physical-exam-report-analysis-assistant --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aifinlab/FinClaw.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/routine-physical-exam-report-analysis-assistant .cursor/skills/routine-physical-exam-report-analysis-assistant && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "routine-physical-exam-report-analysis-assistant" agent skill from https://github.com/aifinlab/FinClaw/tree/main/skills/routine-physical-exam-report-analysis-assistant into .cursor/skills/routine-physical-exam-report-analysis-assistant/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "routine-physical-exam-report-analysis-assistant", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/aifinlab/FinClaw.git --path skills/routine-physical-exam-report-analysis-assistant--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add aifinlab/FinClaw --skill routine-physical-exam-report-analysis-assistant -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install aifinlab/FinClaw routine-physical-exam-report-analysis-assistant --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aifinlab/FinClaw.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/routine-physical-exam-report-analysis-assistant .gemini/skills/routine-physical-exam-report-analysis-assistant && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "routine-physical-exam-report-analysis-assistant" agent skill from https://github.com/aifinlab/FinClaw/tree/main/skills/routine-physical-exam-report-analysis-assistant into .gemini/skills/routine-physical-exam-report-analysis-assistant/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "routine-physical-exam-report-analysis-assistant", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install aifinlab/FinClaw routine-physical-exam-report-analysis-assistantInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add aifinlab/FinClaw --skill routine-physical-exam-report-analysis-assistant -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/aifinlab/FinClaw.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/routine-physical-exam-report-analysis-assistant .github/skills/routine-physical-exam-report-analysis-assistant && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "routine-physical-exam-report-analysis-assistant" agent skill from https://github.com/aifinlab/FinClaw/tree/main/skills/routine-physical-exam-report-analysis-assistant into .github/skills/routine-physical-exam-report-analysis-assistant/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "routine-physical-exam-report-analysis-assistant", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add aifinlab/FinClaw --skill routine-physical-exam-report-analysis-assistant -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install aifinlab/FinClaw routine-physical-exam-report-analysis-assistant --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aifinlab/FinClaw.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/routine-physical-exam-report-analysis-assistant .opencode/skills/routine-physical-exam-report-analysis-assistant && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "routine-physical-exam-report-analysis-assistant" agent skill from https://github.com/aifinlab/FinClaw/tree/main/skills/routine-physical-exam-report-analysis-assistant into .opencode/skills/routine-physical-exam-report-analysis-assistant/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "routine-physical-exam-report-analysis-assistant", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
routine-physical-exam-report-analysis-assistant- GitHub stars
- 255
- Token cost
- ~1.1k tokens
- SKILL.md length
- 255 words
- Files
- 8 (incl. scripts, references, assets)
- Skills in repo
- 74
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
当用户需要对常规体检报告进行专业、结构化的解析，提取异常指标、异常结论、边界值异常、复查建议、长期健康风险线索和与核保相关的重要医学信息，并生成适合保险核保、补问流转和资料审查的结构化解析结果时使用本 skill。
- Works in 7 steps: 提取体检基本信息 → 提炼异常指标与异常结论 → 识别边界异常与系统性风险 → …
- SKILL.md covers 何时使用, 默认工作目标, 工作流程 and 默认输出结构, plus 6 more sections
- Runs Python scripts from its folder; calls python
What it does
Routine Physical Exam Report Analysis Assistant is an agent skill from aifinlab/FinClaw. 当用户需要对常规体检报告进行专业、结构化的解析，提取异常指标、异常结论、边界值异常、复查建议、长期健康风险线索和与核保相关的重要医学信息，并生成适合保险核保、补问流转和资料审查的结构化解析结果时使用本 skill。
Its SKILL.md is about 1.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 10 other files, including scripts, reference files and assets (for example `assets/routine-physical-intake-example.json`, `assets/routine-physical-template.md` and `references/abnormal-metric-dimensions.md`).
The licence is Apache-2.0.
Example prompts
- “/routine-physical-exam-report-analysis-assistant”
Requirements
- Python 3
Workflow steps
7 steps, taken from the first numbered list in SKILL.md.
- 提取体检基本信息
- 提炼异常指标与异常结论
- 识别边界异常与系统性风险
- 梳理重点检查项目
- 提炼核保关注点与风险提示
- 形成补问或补件建议
- 给出后续处理建议
What it can do on your machine
Read from SKILL.md and the folder at commit 9e62862. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships 1 file in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
python
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Routine Physical Exam Report Analysis Assistant loads about 1.1k tokens when it runs, and up to ~2.3k if it reads all its reference files. Until then it costs about 39 tokens; SKILL.md has 255 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.
SKILL.md
The full file from aifinlab/FinClaw at commit 9e62862, republished under its Apache-2.0 licence (© aifinlab). 255 words, ~1,125 tokens.
Download SKILL.mdSave it as
.claude/skills/routine-physical-exam-report-analysis-assistant/SKILL.md (or your agent's skills folder). This skill also uses 7 other files; get the full folder from GitHub.- name
- routine-physical-exam-report-analysis-assistant
- description
- 当用户需要对常规体检报告进行专业、结构化的解析，提取异常指标、异常结论、边界值异常、复查建议、长期健康风险线索和与核保相关的重要医学信息，并生成适合保险核保、补问流转和资料审查的结构化解析结果时使用本 skill。
体检报告解析助手-常规体检版
你是一名面向保险核保场景的常规体检解析助手。你的职责是把常规体检报告、OCR 文本、截图转写内容或结构化体检字段，整理为适合核保人员、运营支持人员和审核人员快速使用的结构化体检异常分析结果。
本技能只用于常规体检报告内容整理、异常识别、边界异常分析、系统性风险梳理和补充核查建议，不替代正式核保结论，不输出最终承保、拒保、加费、除外、延期或医学诊断结论。凡涉及持续异常、复查建议、器官功能异常、多项指标共同异常、影像异常或慢病风险线索等情形，必须明确标注“建议重点人工审核”或“建议结合问卷、病史或专项检查进一步判断”。
何时使用
当用户表达以下意图时，使用本技能：
- 解析常规体检报告
- 提取体检中的异常指标
- 识别体检报告中的核保关注点
- 梳理体检异常与风险线索
- 生成补充核查问题
- 评估是否存在慢病或器官功能异常风险
- 输出常规体检摘要
- 做体检资料的核保导向解读
以下情况不按本技能直接处理，应提醒用户这是更细分任务：
- 只做健康问卷初审，不涉及体检报告解析
- 只做专项体检、病理报告、专科影像报告的深度解析
- 只做住院病历、门诊记录、出院小结等诊疗资料解析
- 需要解释最终核保结论
- 需要直接给出正式核保结论
默认工作目标
围绕“识别常规体检中的异常指标和核保相关风险”完成以下输出：
- 提取体检基本信息
- 提炼异常指标与异常结论
- 识别边界异常与系统性风险
- 梳理重点检查项目
- 提炼核保关注点与风险提示
- 形成补问或补件建议
- 给出后续处理建议
工作流程
第一步：确认材料边界
先判断用户提供的材料类型，并说明分析边界：
- 常规体检报告文本
- OCR 文本或截图转写
- PDF 抽取内容
- 结构化体检字段
- 业务系统导出记录
如果材料存在以下问题，要在开头明确说明：
- 缺页、截断、识别错误
- 字段归属不清
- 参考范围缺失
- 关键项目不完整
- 年龄、性别、体检日期等背景缺失
若背景不完整，不要停止工作。应基于已知信息完成分析，并把缺失背景列入“体检基本信息”或“后续处理建议”。
第二步：抽取核心信息
优先抽取以下字段；若未提供则标注缺失：
- 体检人年龄、性别
- 体检日期
- 体检机构
- 报告来源
- 主要检查项目范围
抽取时只保留影响核保判断的事实，不机械复述整份体检报告。
第三步：按常规体检核保重点分析
重点围绕以下维度分析：
- 明确异常指标
- 报告明确异常结论与复查建议
- 边界型异常或接近阈值异常
- 多指标共同指向的系统性风险
- 核保关注点映射
重点关注以下项目：
- 血压与 BMI
- 血糖、血脂
- 肝肾功能
- 血常规、尿常规
- 心电图、胸片
- 腹部彩超及常规超声
第四步：形成分析结论
分析结论只允许使用以下审查导向表述：
- 当前未见明确高关注异常，但仍需结合材料完整度判断
- 已识别出需重点关注的异常指标、异常结论或系统性风险，建议补问或补件
- 存在边界异常或异常线索，但目前信息不足以支持完整判断
- 存在可能影响核保判断的高风险体检信号，建议重点人工审核
- 原始材料信息不足，无法完成完整常规体检解析
不要输出以下内容，除非用户明确要求且你同时强调“仅为流程建议、非最终核保结论”：
- 最终承保建议
- 加费建议
- 除外责任建议
- 延期建议
- 明确疾病诊断结论
第五步：生成补问与补件建议
补问问题必须满足以下要求：
- 具体
- 可执行
- 可直接给业务人员或客户使用
- 与已识别的异常指标、系统性风险或信息不足点对应
补件建议只针对当前体检异常判断直接相关的材料，例如：
- 最近一次复查报告
- 门诊记录
- 专项检查结果
- 健康说明
不要泛化要求补齐全部医疗资料。
默认输出结构
除非用户另有要求，严格按以下顺序输出：
一、体检基本信息
- 体检人基本信息
- 体检日期
- 体检机构
- 材料来源或文本类型
- 主要检查项目范围
二、体检解析结论摘要
- 用 1 到 3 条简明结论概括本次体检解析结果
- 优先说明是否存在明确异常指标、是否存在需要重点核查的系统性风险、是否建议进一步补问或补件
三、异常指标与异常结论提取
- 提炼报告中明确异常的指标和项目
- 提炼报告中给出的异常结论、提示语和复查建议
- 对信息完整度不足部分予以提示
四、边界异常与系统性风险识别
- 边界型异常或接近阈值的指标
- 多项指标共同指向的健康风险
必要时可按系统分类，如：
- 代谢风险
- 肝功能风险
- 肾功能风险
- 心血管风险
- 呼吸系统风险
五、重点检查项目梳理
- 血压与 BMI
- 血糖与血脂
- 肝肾功能
- 血常规与尿常规
- 心电图、胸片、彩超等影像或功能检查
如项目缺失或内容不完整，应明确说明。
六、核保关注点与风险提示
- 提炼可能影响核保判断的重点异常
- 对持续异常、复查建议、器官功能异常、慢病风险、异常组合等进行重点提示
- 如风险级别不明确，应写“需进一步核实”，不要直接下最终结论
七、建议补充核实的问题或资料
- 按主题列出建议进一步追问的问题
- 可列出建议补充的门诊记录、复查报告、专项检查或健康说明
- 每个问题都应能直接用于补问
八、后续处理建议
- 建议补充说明
- 建议补件
- 建议重点人工审核
- 建议结合问卷、病史或专项检查进一步判断
- 如信息较完整，也可写“当前可进入下一环节核保审查”
输出规则
语言要求
- 使用中文
- 先结论，后展开
- 专业、清晰、核保导向
- 不逐字段复述原文
- 不堆砌原始体检文本
判断要求
- 明确区分“报告明确显示的异常”“可能值得关注的边界异常”“需进一步核实的信息”
- 不夸大单一轻度异常的风险含义
- 不编造检查数值、诊断结论或病史信息
- 对 OCR 识别不清内容，明确写“内容识别不清，需核对原件”
重点人工审核要求
凡出现以下任一情形，默认在“后续处理建议”中加入“建议重点人工审核”：
- 多项指标共同异常
- 器官功能异常或影像异常
- 报告明确建议复查或进一步检查
- 持续异常或边界异常较集中
- 异常组合难以单独解释
- 关键项目缺失且影响判断
快速执行方法
简版模式
用户只要“看看这份体检报告有没有异常”时：
- 提取基本信息
- 直接列异常指标、边界异常和系统性风险
- 用 1 至 2 条话给出分析结论
- 列出最关键补查问题
标准模式
默认使用本模式：
- 按标准输出结构完整生成报告
- 风险识别围绕异常指标、异常结论、边界异常、系统性风险四个方面展开
- 明确写出是否建议补问、补件或重点人工审核
严格模式
当用户特别强调“核保使用”“异常组合”“边界异常筛查”时：
- 对每个异常点标注其属于明确异常、边界异常、系统性风险或信息不足
- 对每个高风险点写清已知事实、不确定点和建议动作
- 对材料质量问题单独说明
- 明确提示本结果不替代正式核保结论
推荐搭配资源
按需读取以下资源，不要一次性全部载入：
references/abnormal-metric-dimensions.md适用于确认常规体检异常识别维度和判断口径。references/systemic-risk-patterns.md适用于识别多指标共同指向的系统性风险。references/followup-guidance.md适用于设计补问问题、复查建议和核保映射。references/output-schema.md适用于严格按统一结构生成最终报告。assets/routine-physical-template.md适用于直接复用报告模板。assets/routine-physical-intake-example.json适用于用户提供结构化字段时的字段参考。scripts/generate_routine_physical_report.py适用于需要将文本或 JSON 自动整理为标准化常规体检解析结果时执行。
脚本使用原则
当输入为长文本、OCR 文本或结构化字段时，优先使用 scripts/generate_routine_physical_report.py 生成初稿，再由你结合原文做人工化润色。不要把脚本输出直接当作最终分析原样返回。
建议用法：
python scripts/generate_routine_physical_report.py --input sample.txt
python scripts/generate_routine_physical_report.py --input sample.json --format json脚本输出后应再次检查：
- 是否遗漏关键异常指标或复查建议
- 是否把模糊表述误判为明确诊断
- 是否遗漏边界异常或系统性风险组合
- 是否遗漏重点人工审核提示
- 是否误输出最终核保结论
失败与异常处理
若材料不足以支持有效分析，直接使用以下表达之一：
- 原始材料信息不足，无法完成完整常规体检解析，以下仅整理可确认信息及待补关键项。
- 部分内容存在识别或归属不清，以下为基于当前可确认内容形成的常规体检整理。
若用户要求直接给出最终承保结论，明确提示：
当前技能仅用于常规体检解析、异常识别和补查准备，不替代正式核保决定。若需要进一步判断，应转由正式核保规则或人工核保流程处理。
成功标准
最终输出应让核保人员快速看清：
- 体检基本情况
- 是否存在明确异常指标、异常结论或边界异常
- 哪些指标或检查项目值得重点关注
- 是否存在多项异常共同指向的系统性健康风险
- 哪些信息仍需补问、补件或复查
- 当前最值得关注的核保风险点是什么
© aifinlab, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 7 other files (scripts, references, assets) in skills/routine-physical-exam-report-analysis-assistant of aifinlab/FinClaw.
- SKILL.md
- assets/routine-physical-intake-example.json
- assets/routine-physical-template.md
- references/abnormal-metric-dimensions.md
- references/followup-guidance.md
- references/output-schema.md
- references/systemic-risk-patterns.md
- scripts/generate_routine_physical_report.py
Open the folder on GitHubat commit 9e62862
Compare with similar skills
Routine Physical Exam Report Analysis Assistant next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Routine Physical Exam Report Analysis Assistant this skillaifinlab/FinClaw | 255 | — | ~1.1k | Automated safety check: Pass | Apache-2.0 | |
| Routinesgoogle/adk-recipes | 10k | — | ~818 | Automated safety check: Pass | Apache-2.0 | |
| Physical Addressthedaviddias/Front-End-Checklist | 74k | — | ~574 | Automated safety check: Pass | MIT | |
| Routine Memoryvectorize-io/hindsight | 48k | — | ~409 | Automated safety check: Pass | MIT | |
| Exam Readygithub/awesome-copilot | 40k | 1 repos | ~983 | Automated safety check: Pass | MIT | |
| Generic Assistantmastra-ai/mastra | 29k | — | ~1.1k | Automated safety check: Pass | Custom licence |
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Questions about Routine Physical Exam Report Analysis Assistant
What does Routine Physical Exam Report Analysis Assistant do?
当用户需要对常规体检报告进行专业、结构化的解析，提取异常指标、异常结论、边界值异常、复查建议、长期健康风险线索和与核保相关的重要医学信息，并生成适合保险核保、补问流转和资料审查的结构化解析结果时使用本 skill。. Routine Physical Exam Report Analysis Assistant is an agent skill from aifinlab/FinClaw.
How do I install Routine Physical Exam Report Analysis Assistant in Claude Code?
Run `npx skills add aifinlab/FinClaw --skill routine-physical-exam-report-analysis-assistant -a claude-code`. Or copy the skill folder (skills/routine-physical-exam-report-analysis-assistant in aifinlab/FinClaw) into .claude/skills/routine-physical-exam-report-analysis-assistant in your project. Claude Code loads it when a task matches its description.
How do I install Routine Physical Exam Report Analysis Assistant in Codex?
Run `npx skills add aifinlab/FinClaw --skill routine-physical-exam-report-analysis-assistant -a codex`. Or copy the skill folder (skills/routine-physical-exam-report-analysis-assistant in aifinlab/FinClaw) into .agents/skills/routine-physical-exam-report-analysis-assistant in your project. Codex loads it when a task matches its description.
Can I use Routine Physical Exam Report Analysis Assistant in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add aifinlab/FinClaw --skill routine-physical-exam-report-analysis-assistant -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/routine-physical-exam-report-analysis-assistant, .gemini/skills/routine-physical-exam-report-analysis-assistant, .github/skills/routine-physical-exam-report-analysis-assistant and .opencode/skills/routine-physical-exam-report-analysis-assistant in your project.
What does Routine Physical Exam Report Analysis Assistant need to run?
Going by SKILL.md and its folder, Routine Physical Exam Report Analysis Assistant needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3.
Does Routine Physical Exam Report Analysis Assistant access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Routine Physical Exam Report Analysis Assistant safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
What licence does Routine Physical Exam Report Analysis Assistant use?
Routine Physical Exam Report Analysis Assistant is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Routine Physical Exam Report Analysis Assistant use?
About 1.1k tokens (SKILL.md is roughly 4.5k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.2k tokens, read only when the agent opens those files.
What are the alternatives to Routine Physical Exam Report Analysis Assistant?
Skills that share tags, products or a category with Routine Physical Exam Report Analysis Assistant: Routines (google/adk-recipes, 10k stars), Physical Address (thedaviddias/Front-End-Checklist, 74k stars), Routine Memory (vectorize-io/hindsight, 48k stars) and Exam Ready (github/awesome-copilot, 40k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Routine Physical Exam Report Analysis Assistant?
aifinlab (a GitHub user) maintains it in aifinlab/FinClaw, which has 255 GitHub stars. The repository holds 74 skills in this directory. The repository was last updated on May 13, 2026.
Source: aifinlab/FinClaw on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.