stock-goodwill-predict skillA
stock-goodwill-predict is agent-read markdown (skill) from ftshare-lab/ftshare-skill: Get goodwill impairment prediction data (商誉减值预期) for stocks. Use when user asks about 商誉减值预期, 商誉减值预告, 业绩预告, goodwill impairment prediction, goodwill forecast..
Indexed from public GitHub and served as immutable, content-addressed versions. Install it pinned to an exact SHA-256 with the mdr CLI, and every file is verified against the hash recorded here before it reaches your agent. The deterministic audit below grades the latest version, and the same file always earns the same grade.
What the file says
# 查询商誉减值预期明细
## 接口说明
| 项目 | 说明 |
|------|------|
| 接口名称 | 查询商誉减值预期明细 |
| 外部接口 | GET /api/v1/market/data/goodwill/predict |
| 请求方式 | GET |
| 适用场景 | 查询商誉减值业绩预告数据，包含预测净利润上下限、业绩变动幅度、上年同期净利润等字段 |
## 请求参数
说明：date 为必填项。
| 参数名 | 类型 | 是否必填 | 描述 | 取值示例 | 备注 |
|--------|------|----------|------|----------|------|
| date | string | 是 | 报告期日期 | 20251231 | 格式 YYYYMMDD，按年份范围过滤，如 20251231 查询 2025 全年 |
## 执行方式
```bash
python scripts/handler.py --date 20251231
```
## 响应结构
```json
{
"code": 0,
"message": "success",
"data": {
"pageNum": 1,
"pageSize": 50,
"total": 820,
"pages": 17,
"records": [
{
"seq": 0,
"security_code": "601211",
"security_name": "国泰海通",
"perform_change_explain": "业绩变动原因说明...",
"predict_period": "20251231",
"newest_goodwill": "10000000000.0000",
"goodwill_previous": "9500000000.0000",
"predict_netprofit_lower": "50000000000.0000",
"predict_netprofit_upper": "60000000000.0000",
"perform_change_lower": "10.50000000",
"perform_change_upper": "20.50000000",
"pe_samereport_netprofit": "45000000000.0000",
"notice_date": "2025-04-01 00:00:00",
…Read the whole file at its exact version.
How to install
mdr add ftshare-lab/ftshare-skill/stock-goodwill-predict@git:20260916.8724d04mdr add ftshare-lab/ftshare-skill/stock-goodwill-predict@sha256:5c21a70600e4630cPin to a label to follow the author's releases, or to a sha256 to freeze the exact bytes forever. Either way the resolved hash is written to mdr.lock, and mdr install reproduces it on any machine.
[](https://markdownregistry.com/a/art_n6dgzn2gfqqdrgnk)
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Versions
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (3094 bytes)
- pass: No zero-width or bidi control characters
- pass: No instruction hidden inside an HTML comment
- pass: No link to an exfiltration or paste host
- pass: No credential-shaped string
- pass: No instruction to send local credentials anywhere
- pass: No text hidden with inline styles
- pass: No prompt-injection phrasing
- pass: No curl or wget piped into a shell
- pass: No recursive delete of root, home or parent
- pass: No instruction to read or print local credentials
- pass: No base64 blob over 200 characters
- pass: No link to a raw IP address
- pass: No script tag
Source
ftshare-lab/ftshare-skill · 64 stars · license MIT · pushed 2026-09-22 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_n6dgzn2gfqqdrgnk GET https://markdownregistry.com/api/v1/resolve?ref=ftshare-lab/ftshare-skill/stock-goodwill-predict GET https://markdownregistry.com/api/v1/blob/5c21a70600e4630c1b08b7111870dfe2e29c01519b78536ca90197367262ebac
Your agent does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.