basket-analysis

basket-analysis is a skill for Claude Code, Codex from coffee-man666/mommy-chaogu. It costs 435 tokens per session (3,826 once invoked), scanned A, original, MIT.

A repeatable workflow for analyzing a theme-based basket of stocks listed on China’s A-share market. It selects or builds a 10–50-stock group, checks money flow, technical indicators, valuation and profitability, then ranks the top five.

In plain words
What is it for?
Use it for themes such as semiconductors, coal, innovative medicines, or new energy, with a chosen trading day and optional run label; it produces the defined analysis artifacts and report package.
Why use it?
It gives different themes the same analysis method while allowing each theme to define its own basket and background checks. This makes theme research more consistent and easier to reproduce.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it for themes such as semiconductors, coal, innovative medicines, or new energy, with a chosen trading day and optional run label; it produces the defined analysis artifacts and report package.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/coffee-man666/mommy-chaogu/basket-analysis
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add coffee-man666/mommy-chaogu --skill basket-analysis
Clone the repo
git clone --depth 1 https://github.com/coffee-man666/mommy-chaogu

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for basket-analysis

README.md
[![agentmods](https://agentmods.dev/badge/skills/coffee-man666/mommy-chaogu/basket-analysis/github.svg)](https://agentmods.dev/skills/coffee-man666/mommy-chaogu/basket-analysis)
Your own site
<a href="https://agentmods.dev/skills/coffee-man666/mommy-chaogu/basket-analysis"><img src="https://agentmods.dev/badge/skills/coffee-man666/mommy-chaogu/basket-analysis/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.

agentmods 80×15 button for basket-analysis

Your own site · 80×15
<a href="https://agentmods.dev/skills/coffee-man666/mommy-chaogu/basket-analysis"><img src="https://agentmods.dev/badge/skills/coffee-man666/mommy-chaogu/basket-analysis.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 435 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,826 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 2 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00435 $0.03826
Opus 5 $0.00217 $0.01913
Sonnet 5 $0.00087 $0.00765
Haiku 4.5 $0.00044 $0.00383

Measured 12d ago against content hash 5a0138efd60a, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

basket-analysis scanned grade A with 2 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 12d ago.

The scan reads SKILL.md. This mod also ships 5 executable files (scripts/analyze.py, scripts/html_render.py, scripts/package_zip.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

- `retry_kline()` → built-in (used by agent when fetching K-line via urllib)

Runs shell commandslowCapability

Expected in a hook, worth knowing in a rule or an instructions file.

- **`retry_with_backoff(fn, max_attempts=3, initial_delay=2, backoff_factor=2, max_delay=30, jitter=0.3)`** — generic decorator. Retries on `URLError`, `HTTPError`, `TimeoutError`, `ConnectionError`, `OSError`, `subproce
src/mommy_chaogu/bundled_skills/basket-analysis/SKILL.md · 203 lines

How it starts

The opening of the file, as written. The whole thing — 203 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Basket Analysis (通用 A 股主题篮子分析)

End-to-end pipeline that takes a trading day (default: today, Beijing time) and a theme name (e.g. 粮食安全, 半导体, 煤炭, 创新药), and produces a packaged set of analysis artifacts for that theme's basket.

主题配置 (theme config)

所有主题共用同一套技术方法 (10 步 procedure). 主题间的差异 (篮子, 4 变量触发, 全局背景, 搜索关键词) 都封装在 references/themes/{theme}.md 配置里.

当前内置主题:

  • references/themes/food-security.md — 粮食安全/危机 (35 只, FAO + 黑海 + 厄尔尼诺 + 399365 PE)
  • references/themes/_template.md — 新主题模板 (复制此文件 + 改 4 变量即可)

加新主题: cp references/themes/_template.md references/themes/my-theme.md 然后填:

  • basket.source (mommy CLI / SQL group / 手动列表)
  • trigger_variables (4 个变量 + 搜索 query)
  • global_context_searches (必查的全局背景)
  • domain_keywords (主题关键词, 用于篮子筛选)

Inputs to collect

Ask the user only what the procedure cannot infer:

  • Theme name (default: food-security). 必填, 决定 basket + 4 变量 + 报告标题.
  • Trading day (default: today Beijing time). Required if back-fill ("复盘 8/15").
  • Run label (default: auto-timestamp).
  • Mark as final (default: false if multiple runs already today, true if first or only run).

If the user is vague ("复现刚才的分析"), use the last-used theme + today's date.

Procedure

  1. Resolve theme + trading day + data freshness

    • Theme: from user input (or default food-security). Load references/themes/{theme}.md to get basket source + 4 variable definitions + search queries.
    • Trading day: today_bj = now(Asia/Shanghai).strftime("%Y-%m-%d") + now_bj_iso with +08:00.
    • Detect post-market: if now_bj.time() > 15:05, mark is_market_close=true. Otherwise mid-day (Beijing).
    • Why: theme drives everything downstream; data label is what readers see.
  2. Verify basket exists for the theme

    • Read the theme config's basket.source. If mommy <cli>, run mommy <cli> list and mommy <cli> stats. If manual, ensure the list is provided. If basket_totallen(pulled), may need to seed first.
    • Confirm 4 chain/subcategory (or whatever the theme config requires). If missing, run mommy <cli> seed first.
    • Why: the basket is the canonical reference; missing seed → downstream flows are incomplete.

Read the full file on GitHub · 203 lines

Changes

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.

  1. 12d ago First seen · 203 lines · 435 tokens per session scan A 5a0138efd60a

Subscribe to this mod's changes

basket-analysis is a skill published in the GitHub repository coffee-man666/mommy-chaogu (47 stars, last pushed today), licensed MIT. It adds 435 tokens to every session and 3,826 once invoked, about $0.0022 per session on Opus 5. A static security scan graded it A with 2 findings (makes network calls, runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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