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 alpacahq/alpaca-skills --skill paper-tradinggit clone --depth 1 https://github.com/alpacahq/alpaca-skillsWrote 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/alpacahq/alpaca-skills/paper-trading)<a href="https://agentmods.dev/skills/alpacahq/alpaca-skills/paper-trading"><img src="https://agentmods.dev/badge/skills/alpacahq/alpaca-skills/paper-trading/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/alpacahq/alpaca-skills/paper-trading"><img src="https://agentmods.dev/badge/skills/alpacahq/alpaca-skills/paper-trading.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 2 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Excessive Agency · line 41 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
- medium Excessive Agency · line 756 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00095 | $0.09977 |
| Opus 5 | $0.00048 | $0.04988 |
| Sonnet 5 | $0.00019 | $0.01995 |
| Haiku 4.5 | $0.00010 | $0.00998 |
Grade A, and why
alpaca-trading-paper-trading scanned grade A with 1 finding 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
- Direct REST API calls via `curl`, `httpx`, `requests`, or any HTTP client How it starts
The opening of the file, as written. The whole thing — 784 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Alpaca Paper Trading
Use this skill when you want your AI agent to preview, submit, inspect, and manage paper-trading orders using Alpaca's Trading API.
This skill is written for you, a Trading API user working with your own Alpaca paper-trading account, credentials, and local workspace. Your agent should make assumptions visible, protect secrets, and confirm order details before submission.
This is the generic (implementation-agnostic) version of the paper-trading skill. It describes the workflow, safety gates, and output contract without binding to any specific execution tool. You can use the Alpaca Python SDK (alpaca-py), the REST API directly, JavaScript/TypeScript, Go, C#, or any tool that speaks to the Trading API. CLI-specific and MCP-specific companion skills exist for users who prefer those execution paths — see §10 for links.
0 - How your AI agent should use this skill
-
Start with your job. Identify what the signal is — a backtest output, a manual trade idea, a scheduled trigger, or an automated system event. Your agent reads any associated context (backtest run folder, strategy description, alert payload) to understand the intent.
-
Reiterate the strategy logic. Your agent restates the strategy interpretation in plain language — entry/exit conditions, indicator parameters, position sizing, and any assumptions — and confirms with you that the interpretation is correct before proceeding.
-
Gather and confirm ALL detailed configurations before execution. Your agent collects every order parameter explicitly:
- Timing of execution (immediate, scheduled, conditional)
- Asset class (US equity, US options, crypto)
- Symbol(s)
- Side (buy / sell)
- Quantity or notional amount
- Order type (market, limit, stop, stop_limit, trailing_stop)
- Time-in-force (day, gtc, ioc, fok, opg, cls)
- Limit price and/or stop price if applicable
- Extended-hours flag
- Risk controls (max position size, max notional, stop-loss, take-profit)
- Margin usage
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 · 784 lines · 95 tokens per session scan A 0c9f90ca6af4
alpaca-trading-paper-trading is a skill published in the GitHub repository alpacahq/alpaca-skills (147 stars, last pushed 3d ago), licensed Apache-2.0. It adds 95 tokens to every session and 9,977 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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