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 ansem-cryptogit 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/ansem-crypto)<a href="https://agentmods.dev/skills/questflowai/investorskills/ansem-crypto"><img src="https://agentmods.dev/badge/skills/questflowai/investorskills/ansem-crypto/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/ansem-crypto"><img src="https://agentmods.dev/badge/skills/questflowai/investorskills/ansem-crypto.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 | $0.00041 | $0.00685 |
| Opus 5.5 | $0.00016 | $0.00274 |
| Sonnet 5.5 | $0.00008 | $0.00137 |
| Haiku 4.5 | $0.00004 | $0.00068 |
Grade A, and why
ansem-crypto 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 1mo 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 — 89 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Ansem Crypto
Use this skill to apply an Ansem-style crypto judgment framework: combine long-term crypto theses, ecosystem rotation, app-token discovery, comparative valuation, technical confirmation, and attention/liquidity reflexivity before the broader market fully prices it.
When To Use
Use this skill when the user asks for:
- Crypto narrative analysis
- Memecoin or community-token evaluation
- Solana ecosystem momentum reads
- L1 versus application-token relative value
- 70/30 core/speculative portfolio structuring
- Attention and social distribution as market signals
- Whether a crypto trade has reflexive upside or is already crowded
Trigger phrases include Ansem, crypto narrative, attention, memecoin, Solana rotation, community, CT, mindshare, and retail flow.
Do Not Use When
- The token is illiquid or cannot be exited.
- The user wants long-only business-quality equity analysis.
- The setup depends only on influencer promotion with no organic community or liquidity.
- The trade has no invalidation, no liquidity, and no position-sizing discipline.
Inputs Needed
- Token, chain, contract, exchange, or ecosystem
- Whether this is a core holding or speculative 30% bucket idea
- Market cap, FDV, liquidity, unlocks, and holder distribution
- Price trend, volume, and relative strength vs majors
- Fundamentals/use case, ecosystem traction, social attention, community activity, narrative, and catalyst path
- Position size, time horizon, and max loss if sizing is requested
Process
- Classify the idea: core major, L1/ecosystem beta, app token, memecoin, or short-term trade.
- Identify the narrative and why it can attract incremental attention or usage.
- Compare valuation across peers: market cap, FDV, market share, and relative upside.
- Check whether price, liquidity, and technical structure confirm the thesis.
- Separate organic community growth from paid or circular promotion.
- Define entry, invalidation, take-profit zones, rotation risk, and journal review.
- Size smaller for high-volatility memecoins and illiquid tokens.
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.
- 1mo ago First seen · 89 lines · 41 tokens per session scan A d419b778e8ed
ansem-crypto is a skill published in the GitHub repository questflowai/investorskills (1,882 stars, last pushed 2mo ago), licensed MIT. It adds 41 tokens to every session and 685 once invoked, about $0.0002 per session on Opus 5.5. 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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