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 marks-cyclesgit 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/marks-cycles)<a href="https://agentmods.dev/skills/questflowai/investorskills/marks-cycles"><img src="https://agentmods.dev/badge/skills/questflowai/investorskills/marks-cycles/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/marks-cycles"><img src="https://agentmods.dev/badge/skills/questflowai/investorskills/marks-cycles.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 | $0.00031 | $0.00530 |
| Opus 5 | $0.00015 | $0.00265 |
| Sonnet 5 | $0.00006 | $0.00106 |
| Haiku 4.5 | $0.00003 | $0.00053 |
Grade A, and why
marks-cycles 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 10d 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.
How it starts
The opening of the file, as written. The whole thing — 81 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Howard Marks Cycles
Use this skill to apply Howard Marks-style cycle and risk judgment: identify where markets are in the cycle, compare price to value and risk premium, and decide whether to be defensive or aggressive.
When To Use
Use this skill when the user asks for:
- Market cycle diagnosis
- Credit spread and risk premium review
- Second-level thinking on a crowded view
- Defensive or aggressive portfolio posture
- Whether risk is being rewarded or ignored
Trigger phrases include Howard Marks, cycle, second-level thinking, risk premium, credit cycle, defensive, aggressive, and market psychology.
Do Not Use When
- The user needs a precise technical entry only.
- There is no market, valuation, credit, or sentiment context.
- The user asks for a prediction without uncertainty ranges.
- The setup requires leverage or forced timing.
Inputs Needed
- Asset class or market
- Valuation, yield, spread, or risk premium data
- Credit conditions, liquidity, default risk, and refinancing risk if relevant
- Sentiment, positioning, and consensus view
- Portfolio exposure and drawdown tolerance if posture is requested
Process
- Identify the cycle: early, mid, late, stressed, panic, recovery.
- Separate first-level view from second-level view.
- Compare price, value, and risk premium.
- Assess market psychology: fear, greed, complacency, forced selling.
- Decide posture: defensive, neutral, opportunistic, or aggressive.
- Size by margin for error, not confidence alone.
Output Format
# Marks Cycle View: [Market]
## Verdict
Defensive / Neutral / Opportunistic / Aggressive / Stand Down
## Cycle Position
## First-Level vs Second-Level View
## Risk Premium
## Market Psychology
## Portfolio Posture
## What Would Change The View
## Missing Data
Guardrails
- Do not forecast with false precision.
- Do not treat high returns as low risk.
- Do not become aggressive when risk is underpriced.
- Do not become paralyzed during panic if compensation is attractive.
- Always ask what is already in the price.
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.
- 10d ago First seen · 81 lines · 31 tokens per session scan A fe75cc9df0e2
marks-cycles is a skill published in the GitHub repository questflowai/investorskills (1,845 stars, last pushed 18d ago), licensed MIT. It adds 31 tokens to every session and 530 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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