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 mickpletcher/AI-Skills --skill alpaca-tradinggit clone --depth 1 https://github.com/mickpletcher/AI-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/mickpletcher/ai-skills/alpaca-trading)<a href="https://agentmods.dev/skills/mickpletcher/ai-skills/alpaca-trading"><img src="https://agentmods.dev/badge/skills/mickpletcher/ai-skills/alpaca-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/mickpletcher/ai-skills/alpaca-trading"><img src="https://agentmods.dev/badge/skills/mickpletcher/ai-skills/alpaca-trading.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00053 | $0.01912 |
| Opus 5.5 | $0.00021 | $0.00765 |
| Sonnet 5.5 | $0.00011 | $0.00382 |
| Haiku 4.5 | $0.00005 | $0.00191 |
Grade A, and why
alpaca-trading 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 — 187 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Alpaca Trading
Intent
Support safe paper trading, Alpaca automation, broker workflow analysis, and Trading repo changes without increasing live trading risk.
Do Not Use When
- Do not use for financial advice, guaranteed performance claims, live order execution without explicit user instruction, or unrelated trading platforms.
- Required context is missing and cannot be reasonably inferred.
- A more specific skill in this repo is a better match.
Use this skill when the user is working in the Trading repository on Alpaca-connected scripts, backtesting workflows, journaling, scheduling, or reusable PowerShell Alpaca modules.
Trigger When
- The user mentions the
Tradingrepo, Alpaca scripts, paper trading, backtesting, journaling, scheduler jobs, or Alpaca PowerShell modules. - The task touches
Alpaca/,Backtesting/,Journal/,Scheduler/,src/,Tests/,rsi_macd_bot/, orbtc-signal-executor/. - The user wants to build, extend, debug, document, test, or review repo workflows around Alpaca trading.
Repo Shape
The current repository is a mixed Python and PowerShell project with these main areas:
Trading/
|-- Alpaca/
|-- Backtesting/
|-- Journal/
|-- Scheduler/
|-- src/
|-- Tests/
|-- rsi_macd_bot/
`-- btc-signal-executor/
Use the existing structure instead of inventing a new module layout.
Default Behavior
- Preserve what already exists unless the user asks for a larger redesign.
- Prefer additive scaffolding over speculative rewrites of trading logic.
- Default to paper-trading-safe patterns and make live-trading risk explicit.
- Keep API secrets in environment variables or existing repo config flows, never hardcoded.
- Align with the repo's existing GitHub Spec workflow for non-trivial changes.
Workflow
- Identify which existing repo area the change belongs to.
- Read the nearby README, script, or module before proposing changes.
- Reuse current patterns for Python, PowerShell, logging, and tests.
- For non-trivial work, follow the repo workflow: requirements, spec, plan, tasks, implementation, audit, regression test.
- Prefer paper-trading examples unless the user explicitly asks for live-trading support.
- If live-trading code is requested, require explicit confirmation patterns and keep the safety guard intact.
- Update docs and tests alongside behavior changes.
What ships with it
4 files 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 · 187 lines · 53 tokens per session scan A 2e0c7187ade7
alpaca-trading is a skill published in the GitHub repository mickpletcher/AI-Skills (20 stars, last pushed 2d ago), licensed MIT. It adds 53 tokens to every session and 1,912 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.
Other skills, from other repositories
agent-spending-mandate
Write a spending mandate that lets an AI agent buy things for you within strict limits: what it may buy, from whom, up to how much per purchase and in total, until when, and what needs your yes. Use when asked to let my agent make purchases, set a budget for an AI shopping agent, allow agentic checkout, limit what my…
kyc-escalation
Write an internal KYC/AML escalation memo: a factual time-stamped trigger description, customer-profile vs activity mismatch analysis, red-flag taxonomy mapping, outstanding information, and a recommendation with rationale. Use when asked to escalate a KYC alert, document an AML concern, write up unusual-activity…
agent-era-pricing
Redesign seat-based pricing for the agent era — when one human runs ten agents, per-seat models collapse. Use when agents are eroding seat counts, when asked to migrate to usage- or outcome-based pricing, to price an agent/API tier, or to defend revenue as customers automate their own usage. Produces a pricing…
ai-roi-audit
Audit whether the organisation's AI spend actually paid — measured against baselines, not vendor math or vibes. Use when a CFO asks what the AI tools returned, when renewing AI contracts, when consolidating overlapping AI subscriptions, or to build the measurement plan before the next spend. Produces an ROI audit with…
credit-memo
Write a credit memo for a lending decision: borrower story, facility structure, repayment sources, financial-ratio spread with covenant headroom, risk factors with mitigants, risk-rating rationale, and a recommendation. Use when asked to write a credit memo, credit application, credit paper, loan write-up, or prepare…
lending-risk-brief
Write a portfolio-level lending risk brief: concentration analysis by sector, geography and single name, vintage performance, migration matrix narrative, macro-sensitivity scenarios, top watch names, and actions. Use when asked to write a portfolio risk report, credit risk committee brief, loan book review, or…