Borrowing it
Nothing to install: this file belongs to huifer/WellAlly-health. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/huifer/WellAlly-health/main/.claude/skills/mental-health-analyzer/SKILL.mdgit clone --depth 1 https://github.com/huifer/WellAlly-healthWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/huifer/wellally-health/mental-health-analyzer)<a href="https://agentmods.dev/skills/huifer/wellally-health/mental-health-analyzer"><img src="https://agentmods.dev/badge/skills/huifer/wellally-health/mental-health-analyzer/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/huifer/wellally-health/mental-health-analyzer"><img src="https://agentmods.dev/badge/skills/huifer/wellally-health/mental-health-analyzer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00047 | $0.08344 |
| Opus 5 | $0.00023 | $0.04172 |
| Sonnet 5 | $0.00009 | $0.01669 |
| Haiku 4.5 | $0.00005 | $0.00834 |
Grade A, and why
mental-health-analyzer scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 982 lines — stays where its author put it; the contents beside it link to each section on GitHub.
心理健康分析技能
核心功能
心理健康分析技能提供全面的心理健康数据分析功能，帮助用户追踪心理状态、识别情绪模式、监测危机风险和优化应对策略。
主要功能模块：
- 心理健康评估分析 - PHQ-9/GAD-7等量表评分趋势分析
- 情绪模式识别 - 识别常见情绪、触发因素和应对方式效果
- 心理治疗进展追踪 - 治疗目标达成和症状改善评估
- 危机风险评估 - 多级危机风险检测（高/中/低）和预警
- 睡眠-心理关联分析 - 睡眠质量与心理状态的关联性分析
- 运动-情绪关联分析 - 运动与情绪改善的关系分析
- 营养-心理关联分析 - 饮食对情绪和焦虑的影响分析
- 慢性病-心理关联分析 - 慢性疾病与心理健康的关系分析
触发条件
技能在以下情况下自动触发：
- 用户使用
/mental trend查看心理状况趋势 - 用户使用
/mental pattern分析情绪模式 - 用户使用
/mental therapy progress查看治疗进展 - 用户使用
/crisis assessment进行危机风险评估 - 用户使用
/mental report生成心理健康报告
医学安全边界
本技能不能做的事：
- ❌ 不进行心理疾病诊断
- ❌ 不开具精神药物处方
- ❌ 不预测自杀风险或自伤行为
- ❌ 不替代专业心理治疗
- ❌ 不处理急性精神危机
本技能能做的事：
- ✅ 识别心理健康趋势和模式
- ✅ 评估危机风险等级并发出预警
- ✅ 提供应对策略建议（非治疗性）
- ✅ 追踪治疗进展和目标达成
- ✅ 提供就医建议和专业资源信息
- ✅ 分析心理健康与其他健康因素的关联
执行步骤
第1步：数据读取
读取心理健康数据文件：
data-example/mental-health-tracker.json- 主心理健康档案data-example/mental-health-logs/.index.json- 日志索引data-example/mental-health-logs/YYYY-MM/YYYY-MM-DD.json- 每日情绪日记
数据验证：
- 检查文件是否存在
- 验证数据结构完整性
- 确认有足够的数据点进行分析（建议至少3次PHQ-9/GAD-7评估，或7天情绪日记）
第2步：心理健康评估趋势分析
PHQ-9抑郁评分趋势分析：
- 分析不同时间点的PHQ-9评分
- 计算评分变化速率（分/月）
- 识别严重程度变化（无/轻度/中度/重度）
- 检测PHQ-9第9项（自伤意念）的变化
- 预测未来趋势（改善/稳定/恶化）
- 与治疗进展关联分析
GAD-7焦虑评分趋势分析：
- 分析GAD-7评分时序变化
- 识别焦虑症状变化模式
- 关联触发因素与焦虑水平
- 评估应对方式效果
- 预测焦虑趋势
PSQI睡眠质量与心理状态关联：
- PSQI评分与PHQ-9/GAD-7评分的相关性
- 睡眠障碍对情绪的影响
- 睡眠改善与心理状态改善的关系
严重程度变化检测：
- 识别严重程度升级（需要关注）
- 识别严重程度降级（积极信号）
- 检测快速恶化（≥5分/月，危机预警）
- 检测快速改善（强化有效策略）
第3步：情绪模式识别
常见情绪统计：
- 统计最常见的主要情绪（top 5）
- 计算平均情绪强度
- 识别情绪分布模式
- 分析情绪多样性
时间模式分析：
- 一天中的情绪变化模式（早/中/晚）
- 一周中的情绪变化模式（周一至周日）
- 情绪波动程度（方差/标准差）
- 情绪稳定性评估
触发因素分析：
- 统计高频触发因素（top 10）
- 计算每个触发因素的平均影响
- 识别高危触发因素（高影响+高频）
- 触发因素与情绪类型的关联
应对方式效果评估：
- 计算每种应对方式的有效性（有帮助/没帮助的比例）
- 识别高效应对策略（>80%有效）
- 识别低效应对策略（<50%有效）
- 应对方式与情绪类型的匹配分析
第4步：心理治疗进展追踪
治疗目标达成评估：
- 计算每个目标的完成百分比
- 评估症状改善程度（基线→当前→目标）
- 预估目标达成时间
- 识别滞后目标（需要调整）
治疗过程分析：
- 治疗频率和依从性
- 作业完成率和质量
- 治疗联盟强度
- 咨询前后情绪变化
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 982 lines · 47 tokens per session scan A 0b67fb34380e
mental-health-analyzer is a skill published in the GitHub repository huifer/WellAlly-health (948 stars, last pushed 1mo ago), licensed MIT. It adds 47 tokens to every session and 8,344 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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