uwillberich

uwillberich is a skill for Claude Code, Codex from Lord1Egypt/awesome-skill-forge. It costs 63 tokens per session (1,697 once invoked), scanned A, original, MIT.

A workflow for planning the next trading session in China's A-share stock market. It combines market structure, overnight events, policy timing, sector leadership, watchlists, and capital-flow signals.

In plain words
What is it for?
Use it to prepare before the open, assess likely recovery sectors, monitor the first 30 minutes, update watchlists from news and industry links, and evaluate market sentiment.
Why use it?
It turns scattered market information into a concrete plan for the next session. It helps distinguish a broad market recovery from a rise concentrated in defensive sectors.

Skill for Claude CodeCodex

Which agent this was written for is unclear — built for openclaw. Also seen: built for openclaw.

Good fit Use it to prepare before the open, assess likely recovery sectors, monitor the first 30 minutes, update watchlists from news and industry links, and evaluate market sentiment.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/lord1egypt/awesome-skill-forge/a-share-decision-desk
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 Lord1Egypt/awesome-skill-forge --skill a-share-decision-desk
Clone the repo
git clone --depth 1 https://github.com/Lord1Egypt/awesome-skill-forge

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 uwillberich

README.md
[![agentmods](https://agentmods.dev/badge/skills/lord1egypt/awesome-skill-forge/a-share-decision-desk/github.svg)](https://agentmods.dev/skills/lord1egypt/awesome-skill-forge/a-share-decision-desk)
Your own site
<a href="https://agentmods.dev/skills/lord1egypt/awesome-skill-forge/a-share-decision-desk"><img src="https://agentmods.dev/badge/skills/lord1egypt/awesome-skill-forge/a-share-decision-desk/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 uwillberich

Your own site · 80×15
<a href="https://agentmods.dev/skills/lord1egypt/awesome-skill-forge/a-share-decision-desk"><img src="https://agentmods.dev/badge/skills/lord1egypt/awesome-skill-forge/a-share-decision-desk.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 63 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,697 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 $0.00063 $0.01697
Opus 5 $0.00032 $0.00848
Sonnet 5 $0.00013 $0.00339
Haiku 4.5 $0.00006 $0.00170

Measured 11d ago against content hash 88772c92730a, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

uwillberich 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 11d 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.

community/clawhub/a/a-share-decision-desk/SKILL.md · 151 lines

How it starts

The opening of the file, as written. The whole thing — 151 lines — stays where its author put it; the contents beside it link to each section on GitHub.

uwillberich

Author: 超超 Contact: [email protected]

Overview

Use this skill for decision-oriented A-share analysis. The goal is not to explain the market mechanically, but to convert today’s tape and overnight developments into a concrete next-session plan.

Best fit:

  • next-session A-share outlook
  • likely repair sectors after a selloff
  • opening checklist for 09:00, 09:25, and 09:30-10:00
  • first-30-minute observation template for distinguishing true repair from defensive concentration
  • watchlist-based decision notes
  • distinguishing defensive leadership from true market repair
  • persistent message iteration that maps high-attention news into watchlist overlays
  • automatic event-driven stock pools that feed directly into desk reports
  • main-force capital-flow confirmation for watchlists and market-wide risk tone
  • industry-chain expansion that turns event themes into fresh stock pools
  • sentiment scoring built from breadth, sector dispersion, and capital flow

Core Workflow

  1. Gather market structure first.
    • Confirm EM_API_KEY is configured before running any script.
    • Run scripts/fetch_market_snapshot.py for indices, breadth, and sector leaders/laggards.
    • Run scripts/fetch_quotes.py or scripts/morning_brief.py for the watchlist.
  2. Confirm the overnight and policy layer.
    • Use primary sources first for PBOC, Federal Reserve, and other central-bank decisions.
    • Use high-quality news sources for geopolitics, oil, and global risk sentiment.
  3. Classify the market through three layers.
    • External shock: oil, rates, U.S. equities, geopolitics
    • Domestic policy/liquidity: LPR, PBOC posture, macro support
    • Internal structure: breadth, leadership, relative strength, style rotation
  4. Build a scenario tree.
    • Provide Base / Bull / Bear paths with explicit triggers and invalidations.
  5. Turn the view into an execution checklist.
    • Include 09:00, 09:20-09:25, 09:30-10:00, and 14:00-14:30.

Workflow Shortcuts

Read the full file on GitHub · 151 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. 11d ago First seen · 151 lines · 63 tokens per session scan A 88772c92730a

Subscribe to this mod's changes

uwillberich is a skill published in the GitHub repository Lord1Egypt/awesome-skill-forge (2 stars, last pushed 3mo ago), licensed MIT. It adds 63 tokens to every session and 1,697 once invoked, about $0.0003 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 2026-08-31.

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