Investor Skills is an open-source library that organizes investing judgment—such as evaluating opportunities, managing risk, and acting under uncertainty—into structured, reusable instructions for people and AI finance agents. It is designed for studying and applying investment approaches, including inside Questflow and other agent tools. The catalogue includes portable skill packages from the library.
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.
npx skills add questflowai/investorskills --skill dengxiaofeng-cycle-industrygit clone --depth 1 https://github.com/questflowai/investorskillsWrote 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/questflowai/investorskills/dengxiaofeng-cycle-industry)<a href="https://agentmods.dev/skills/questflowai/investorskills/dengxiaofeng-cycle-industry"><img src="https://agentmods.dev/badge/skills/questflowai/investorskills/dengxiaofeng-cycle-industry/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/questflowai/investorskills/dengxiaofeng-cycle-industry"><img src="https://agentmods.dev/badge/skills/questflowai/investorskills/dengxiaofeng-cycle-industry.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 | $0.00044 | $0.00429 |
| Opus 5 | $0.00022 | $0.00215 |
| Sonnet 5 | $0.00009 | $0.00086 |
| Haiku 4.5 | $0.00004 | $0.00043 |
Grade A, and why
dengxiaofeng-cycle-industry 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 12d 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.
What it actually says
Deng Xiaofeng Cycle Industry
Use this skill to apply Deng Xiaofeng / 邓晓峰-style judgment.
When To Use
Use this skill when the user asks for:
- cycle industry analysis
- whether an industry is at cycle bottom or top
- deep industry research thesis
- Deng Xiaofeng-style value with cycle awareness
Trigger phrases include 邓晓峰, Deng Xiaofeng, cycle industry, 行业周期, supply demand cycle, 周期底部.
Do Not Use When
- Another skill fits better.
- Critical data for this model is missing.
- The user wants guaranteed returns or unbounded leverage.
- The request is generic chatter with no decision.
Inputs Needed
- Asset, sector, market, or macro context
- Relevant financial, technical, policy, or sentiment data
- Time horizon and risk constraints
- Portfolio context if sizing is requested
Process
- Map the industry cycle: bottom, recovery, peak, downturn.
- Analyze supply-demand dynamics and capacity additions.
- Identify the industry leader with cost/scale advantage.
- Buy at cycle bottom when price reflects pessimism; reduce at cycle top.
Output Format
# Deng Xiaofeng Cycle Industry View: [Subject]
## Verdict
Buy Cycle Bottom / Watch / Cycle Still Falling / At Cycle Top / Pass
## Thesis
## Evidence
## Risks
## Action Plan
## Invalidation
## Missing Data
Guardrails
- Follow the skill process; do not free-style.
- Separate facts, assumptions, and judgment.
- Define invalidation before sizing.
- Not financial advice.
Questflow Use
Use as a judgment module inside Questflow-style agent workflows. Reference readings/podcasts/videos after loading the skill.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 12d ago First seen · 74 lines · 44 tokens per session scan A 26b25b932987
dengxiaofeng-cycle-industry is a skill published in the GitHub repository questflowai/investorskills (1,849 stars, last pushed 19d ago), licensed MIT. It adds 44 tokens to every session and 429 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 2026-08-30.
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