By sogud
Portable investment research skills for source-grounded Dense Calm + ECharts HTML reports with clickable citations, compact tables, and plain-language explanations.
Orchestrate the Alpha Research workflow from a vague market idea to local research artifacts and a final report. Use when the user wants to research a trend, company, material, technology, industry, or market narrative end-to-end.
Reverse-engineer a trend or technology into its supply chain, physical constraints, chokepoints, and related public companies using Serenity-style bottleneck research.
Final synthesis and quality gate for Alpha Research reports. Use after thesis-audit to consolidate prior artifacts, check structure, evidence discipline, risks, anti-hype language, and produce the final professional HTML report.
Plan and collect the first evidence layer for Alpha Research. Use after the research question is clear and before chain tracing, thesis audit, or report synthesis.
Audit an Alpha Research thesis in one pass by classifying claims as Fact, Inference, Assumption, or Rumor, checking citations, and attacking the thesis from the bear side with kill criteria.
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A portable, Markdown-first skill collection for turning vague market ideas into structured, source-grounded, red-teamable investment research reports.
Alpha Research Skills is a source repository for reusable agent skills. It is not a trading bot, financial advisor, brokerage integration, web app, or CLI.
For a quick Pi session from this repository:
cd /Users/changshun/codes/github/alpha-research
pi -e . --name alpha-research-verify
For a global Pi install from a local checkout:
pi install /Users/changshun/codes/github/alpha-research
pi --name alpha-research-verify
For a Pi install from GitHub, use an explicit GitHub source so it is not resolved to another Git host:
pi install git:github.com/sogud/alpha-research
In Pi, skills are invoked with the skill: prefix:
/skill:alpha-research
If Pi is already running after an install, reload resources:
/reload
Common commands:
# Preview
npx plugins discover sogud/alpha-research
# Auto-detect supported targets
npx plugins add sogud/alpha-research
# Install to one target explicitly
npx plugins add sogud/alpha-research --target claude-code
npx plugins add sogud/alpha-research --target cursor
npx plugins add sogud/alpha-research --target codex
# List detected targets
npx plugins targets
If the repository is private, use an SSH URL instead:
npx plugins add [email protected]:sogud/alpha-research.git
Some plugin hosts namespace installed skills, for example /alpha-research:alpha-research. If you want the un-namespaced /alpha-research skill entry, use the Agent Skills installer below.
If you use Claude Code v2.1.142+ with plugin marketplace support:
/plugin marketplace add sogud/alpha-research
/plugin install alpha-research@alpha-research
This is optional Claude Code metadata. The canonical skill source remains skills/.
Use explicit GitHub URLs. Avoid wildcard agent targets; choose the runtime you actually use.
# Claude Code
npx skills add https://github.com/sogud/alpha-research -a claude-code -g -y
# Cursor
npx skills add https://github.com/sogud/alpha-research -a cursor -g -y
# Codex
npx skills add https://github.com/sogud/alpha-research -a codex -g -y
For project-local installs, omit -g if your installer supports it:
npx skills add https://github.com/sogud/alpha-research -a claude-code
git clone https://github.com/sogud/alpha-research.git
cd alpha-research
export AGENT_SKILLS_DIR="$HOME/.agents/skills"
mkdir -p "$AGENT_SKILLS_DIR"
cp -R skills/* "$AGENT_SKILLS_DIR"/
Change AGENT_SKILLS_DIR to your agent's actual skill directory.
After installation, start with one skill:
/alpha-research
English prompt:
Use /alpha-research to research AI optical networking, gold, oil, or another commodity-linked theme.
Run the Alpha Research workflow.
Use strict evidence standards.
You may recommend candidate companies only with data, logic, citations, risks, and failure criteria.
Do not provide direct trade signals, target prices, position sizing, or return guarantees.
Separate Fact, Inference, Assumption, and Rumor.
Produce the final report as `report.html`; Markdown artifacts are only intermediate work products. The default report style is Dense Calm + ECharts: high information density, calm visual surface, compact tables, plain-language explanations, and ECharts SVG figures.
中文 prompt:
使用 /alpha-research 研究 AI 光通信、黄金、原油或其他大宗商品相关主题。
直接运行 Alpha Research 完整研究流程。
使用严格证据标准。
可以推荐候选公司,但必须有数据、逻辑、引用、风险和证伪条件。
不要输出直接交易信号、目标价、仓位建议或收益承诺。
必须区分 Fact、Inference、Assumption、Rumor。
最终输出 Dense Calm + ECharts 风格的单文件 HTML 报告;过程产物可以是 Markdown。
Alpha Research follows a Serenity-style chokepoint research process:
Setup → Orchestrate → Clarify → Profile → Source → Gate → Trace → Audit → Red-team → Synthesis + Quality Gate → Report
flowchart TD
A[Setup]
B[Alpha Research]
C[Thesis Grill]
D[Source Map]
E[Chain Trace]
F[Thesis Audit]
G[Report Quality]
H[Final Report]
A --> B
B --> C
C --> D
D --> E
E --> F
F --> G
G --> H
Alpha Research has a hard source gate: if required primary/data sources, financial baselines, narrative-origin capture, Source Registry entries, citation ids, clickable original-source URLs, or previewable stable locators are missing, the workflow stops before the final report and returns a Source Acquisition Plan.
/thesis-grill → /source-map → /chain-trace → /thesis-audit → /report-quality
Anti-Hype is a stricter research mode for testing popular market narratives, social-media claims, and crowded stories.
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