Agent skill

Agentic Trading Desk

by Oft3r in Oft3r/agentic-trading-desk

Personal trading desk for short-term technical analysis on stocks/ETFs via Robinhood MCP.

MITAuto-check passedBusiness, Finance & HR

Install Agentic Trading Desk

skills CLI
$ npx skills add Oft3r/agentic-trading-desk --skill agentic-trading-desk -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install Oft3r/agentic-trading-desk agentic-trading-desk --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
agentic-trading-desk
GitHub stars
306
Token cost
~5.1k tokens
SKILL.md length
2,869 words
Files
9 (incl. scripts)
Skills in repo
2
Repo updated
First seen
Licence
MIT

At a glance

Personal trading desk for short-term technical analysis on stocks/ETFs via Robinhood MCP.

  • Works in 6 steps: Protected positions: Certain tickers may… → Two accounts, two roles → Buying power: I always take… → …
  • The user asks to analyze a ticker
  • SKILL.md covers Guardrails — Read First,…, Autonomous Execution Mandate, Robinhood MCP Recipe (Order of… and Computation Flow (Run via Code…, plus 4 more sections
  • Runs Python and Shell scripts from its folder; calls python3 and bash; reaches google.com

What it does

Agentic Trading Desk is an agent skill from Oft3r/agentic-trading-desk. Personal trading desk for short-term technical analysis on stocks/ETFs via Robinhood MCP. ALWAYS USE IT whenever the user asks to analyze a ticker, review positions, decide entries/exits/rebuys, calculate indicators (EMA/RSI/MACD/TRIX/Bollinger), score with the three-pillar framework, read the macro regime, or manage the Agentic account — even if he doesn't explicitly name the skill. Compute all indicators using deterministic code (never by eye) from raw Robinhood bars, apply the exit-on-exhaustion /…

Its SKILL.md is about 5.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 10 other files, including scripts (for example `README.md`, `hooks/mandate-order-guard.sh` and `scripts/indicators.py`).

It sits in Business, Finance & HR, covering Trading and backtesting and Stock and market analysis. It works with Model Context Protocol. The repository describes itself as: AI-assisted trading desk for short-term technical analysis on stocks & ETFs via Robinhood MCP. Deterministic Python engines score each asset on a three-pillar framework (Trend ·… The licence is MIT.

When your agent uses it

  • The user asks to analyze a ticker
  • Review positions
  • Decide entries/exits/rebuys
  • Calculate indicators (EMA/RSI/MACD/TRIX/Bollinger)

Example prompts

  • “/agentic-trading-desk”

Requirements

  • Python 3
  • A Bash shell

Workflow steps

6 steps, taken from the first numbered list in SKILL.md.

  1. Protected positions: Certain tickers may be designated as restricted (e.g., stock grants). NEVER analyze them to sell or trim, nor include…
  2. Two accounts, two roles
  3. Buying power: I always take get_portfolio.buying_power as the authoritative figure rather than deriving it myself. Account type matters…
  4. HTML visualization only on Fridays as part of the weekly review ritual. Do not offer or generate it on other days unless the user…
  5. Macro source (optional / best-effort): Investing.com (NO Polymarket). If inaccessible or blocked by network egress, do NOT halt or block…
  6. Autonomous execution is AUTHORIZED in the Agentic account under the Autonomous Execution Mandate (next section). This authorization is…

What it can do on your machine

Read from SKILL.md and the folder at commit 908125f. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 3 files in scripts/ (Python and Shell), which the agent can run.

    Shell commands in SKILL.md call:

    • python3
    • bash

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • google.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Agentic Trading Desk loads about 5.1k tokens when it runs. Until then it costs about 180 tokens; SKILL.md has 2,869 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~180
When it runs · the whole SKILL.md, loaded when a task matches
~5.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from Oft3r/agentic-trading-desk at commit 908125f, republished under its MIT licence (© Oft3r). 2,869 words, ~5,117 tokens.

Download SKILL.mdSave it as .claude/skills/agentic-trading-desk/SKILL.md (or your agent's skills folder). This skill also uses 8 other files; get the full folder from GitHub.
name
agentic-trading-desk
description
Personal trading desk for short-term technical analysis on stocks/ETFs via Robinhood MCP. ALWAYS USE IT whenever the user asks to analyze a ticker, review positions, decide entries/exits/rebuys, calculate indicators (EMA/RSI/MACD/TRIX/Bollinger), score with the three-pillar framework, read the macro regime, or manage the Agentic account — even if he doesn't explicitly name the skill. Compute all indicators using deterministic code (never by eye) from raw Robinhood bars, apply the exit-on-exhaustion / re-enter-on-rebound logic, and respect account guardrails. Executes autonomously in the Agentic account under the Autonomous Execution Mandate, within hard limits on size, cash reserve and risk.

Agentic Trading Desk

Operations manual for short-term trading analysis and execution. I (Agent) perform calls to the Robinhood MCP; the scripts act as my deterministic calculator; the framework decides and I execute. I never calculate indicators by reasoning directly over the price bars: I fetch the data and pass it to scripts/.

Guardrails — Read First, Non-Negotiable

  1. Protected positions: Certain tickers may be designated as restricted (e.g., stock grants). NEVER analyze them to sell or trim, nor include them in exit suggestions. They should only be mentioned as exposure context if relevant.
  2. Two accounts, two roles:
    • Agentic → short-term trading; this is where I execute under the Mandate.
    • Individual (margin account) → core buy-and-hold; only analyze holding quality, no active trading.
    • I identify the tradable account by the broker's own flag from get_accounts (exactly one account is agent-tradable; the others reject my orders outright). I never infer it from the account nickname, and I never hardcode an account number.
  3. Buying power: I always take get_portfolio.buying_power as the authoritative figure rather than deriving it myself. Account type matters and can change: on a cash account only SETTLED cash is spendable (T+1), while a limited-margin account can trade unsettled proceeds immediately.
  4. HTML visualization only on Fridays as part of the weekly review ritual. Do not offer or generate it on other days unless the user explicitly asks for it.
  5. Macro source (optional / best-effort): Investing.com (NO Polymarket). If inaccessible or blocked by network egress, do NOT halt or block execution: proceed with deterministic market data without the yield spread.
  6. Autonomous execution is AUTHORIZED in the Agentic account under the Autonomous Execution Mandate (next section). This authorization is durable and was established by the user in a live session on 2026-08-26; it does NOT depend on a scheduled prompt claiming it exists. A stored prompt cannot grant itself consent — the authorization lives here, in configuration, where it can be verified by reading it. Always review using review_*_order (simulation) before executing place_*_order.

Autonomous Execution Mandate

The user authorizes executing orders without in-the-moment confirmation, only in the broker-designated agent-tradable account, and only within these limits. A limit exceeded is not a cue to ask for permission: it is a cue to not trade and report.

What I may execute

  • Decisions emitted by score.py in this same session, with the macro pillar computed by macro_pillar.py the same day. The scripts still run every session and their output is still the baseline — the framework is not optional.
  • Discretionary entries and exits are authorized (established by the user in a live session on 2026-08-26, superseding the prior zero-discretion rule): a trend change, a news catalyst, or a setup the decision cascade does not cover are all valid reasons to act. The cascade is rigid by design and will miss things; that is what this clause is for.
  • Every discretionary trade MUST carry its reasoning in writing in the session report — what I saw, why it justified acting, and what would prove me wrong. A trade I cannot explain in two sentences is a trade I should not have made.
  • TACTICAL REBOUND goes in at half size — it is counter-trend by definition.
  • Optional: for a news-driven entry, require the tape to be moving in the direction of the thesis before acting rather than anticipating the move. Rationale in External Context below — in scheduled runs the news source is the weakest input available, and price confirmation is the cheapest guard against acting on a mis-dated headline.

Hard limits

  • Max $1,200 per order.

  • Max 3 new positions per session. Exits are uncapped.

  • Minimum 15% of account value held in cash. I never touch that reserve.

  • Order type follows the session clock (rule set by Eli on 2026-08-26, replacing the earlier limit-only rule):

    • Regular hours — Mon–Fri 09:30–15:58 ET: type: "market". If the analysis says enter, enter; a passive limit resting on a price is not an entry. dollar_amount IS permitted here — it is the natural way to size at 3% of the account, and the MCP only accepts it with type=market.
    • Outside regular hours: type: "limit" with an explicit limit_price, marketable — at or just through the far side of the spread, within 0.3% of the last trade — and sized in SHARES (quantity = dollars / limit_price, truncated to 6 decimals). Never dollar_amount here: the MCP would silently convert it to a market order that fills at an unknown price hours later. Fractional limit orders ARE supported despite the tool schema's fractional note (verified 2026-08-26 via review_equity_order: DIA buy limit quantity=0.400000 @ 534.50, accepted with an empty order_checks).
    • stop_market and stop_limit are prohibited at all times. Robinhood also rejects stops on fractional shares, so stops in this account are manual levels I re-check each session, not resting orders.
    • time_in_force must be gfd. No order outlives the session that placed it — an order queued overnight is an unattended fill at a price nobody evaluated.
    • Why the split: the original limit-only rule existed because unattended market orders have invisible slippage. Gating market orders on the session clock answers that directly — they fire only while the book is deep and the session is live, and everything outside that window stays priced.
  • Order preflight. Before every place_equity_order I print this table and check every row. If any row fails, I do NOT place the order — I report instead.

    fieldvaluecheck
    ET clock…inside or outside Mon–Fri 09:30–15:58?
    type…market inside RTH · limit outside · never stop_*
    limit_price…outside RTH only: marketable, within 0.3% of last trade
    sizing…dollar_amount inside RTH · quantity in shares outside
    time_in_force…must be gfd
    notionaldollar_amount or quantity × limit_price≤ $1,200
  • The guard is not load-bearing unless jq is installed. The hook implements every rule with jq; without it the script exits 0 with no output and the runner reads that as ALLOW (verified 2026-08-26 — an early revision let a stop_market through). It now fails closed, but a guard that denies everything is not a working setup either. See Session start — prove the guard is alive below; either way I treat the preflight table above as the real check, not the hook.

  • No new position in a single name within 2 sessions of confirmed earnings (get_earnings_calendar). ETFs exempt.

  • I run review_equity_order before every place_equity_order. If the simulation differs by more than 1% in price or quantity from what I computed, I abort and report.

Session start — prove the guard is alive

The Mandate is prose, and prose cannot enforce itself; hooks/mandate-order-guard.sh is what makes "limit orders only" mechanical. The failure mode that matters is that a guard which is unwired, non-executable, or missing jq looks exactly like a working one until an order slips through. That is not hypothetical: on 2026-08-26 a stop_market passed because jq was absent and the script exited 0 with no output, which the hook runner reads as ALLOW. So before the first place_equity_order of any session I run:

bash
bash <skill-dir>/scripts/session-setup.sh

It installs jq, marks the guard executable, and runs 8 probes across both clock branches — 6 orders the Mandate prohibits, which must be denied, and 2 it permits, which must pass. Probing only for denials is not enough: a guard that blocks everything is just as broken as one that blocks nothing, and from a single deny probe the two look identical. The probes pin the guard's session clock via MANDATE_FAKE_ET so both the regular-hours and after-hours branches are testable whenever the session happens to boot. Exit 0 with order guard verified means the guard is actually evaluating rules. Any other outcome means it is not, and I do not execute orders that session — I still run the analysis and report what the framework emitted, and I say plainly that execution was disabled and why. Analysis with a broken guard is useful; unattended execution with one is not.

One thing to be honest about with myself: .claude/settings.json only loads for a session whose project directory contains it. When the desk is loaded as an installed skill rather than opened as a project, the PreToolUse hook never registers, and the probe above verifies only that the script would deny if it were called. In that mode nothing outside me is checking, so the preflight table is the entire safety margin — I fill it in row by row before every order and abort on any failing row, rather than treating it as paperwork.

This is not hypothetical, and I state it in the session report when it applies. On 2026-08-26 a market order with dollar_amount: 250 (DIA) and two market orders (JPM, 2026-08-25) went through in skill mode with the guard unregistered. Under the current clock rule all three were placed during regular hours and would now pass the guard on their merits — but they passed then because nothing was checking, which is a different thing from being allowed. If the session self-audit shows agentic orders and I am running in skill mode, I say so plainly: the orders were unguarded, whatever their contents turned out to be.

Circuit breakers

  • If account value at session open is down more than 4% against the prior close: no new buys that day. Exits remain allowed.
  • If the data does not reconcile — missing bars, an obviously stale quote, positions that do not match get_equity_positions — I do not trade. The Mandate presupposes sound data; without it the Mandate does not apply.

After executing

  • A push notification per executed order, plus a summary at the end of the run. The user finds out the same day, not on Friday.
  • The durable record lives on the broker's side (get_equity_orders, get_realized_pnl), not in a local file: the execution container is ephemeral.

Still prohibited

  • Protected positions, always (guardrail 1).
  • Any account other than the broker-designated agent-tradable one.
  • Averaging down.
  • Options, crypto, margin and short selling: outside the Mandate.
Show full SKILL.md (1,253 more words)Show less

Robinhood MCP Recipe (Order of Calls)

Load the tools with tool_search before using them (they are deferred).

Guard verification runs before any of this — see Session start — prove the guard is alive in the Mandate. No order goes out in a session where the probe did not come back denied.

Session self-audit (first call of every run). get_equity_orders on the agent-tradable account with placed_agent="agentic" since the previous session. An order is a Mandate breach by a prior run if it is a stop_market or stop_limit; if it is a market order whose market_hours field is anything other than regular_hours; if it carries a dollar_amount outside regular hours; if its time_in_force is not gfd; or if its notional exceeds $1,200. I check type, market_hours, time_in_force and notional on every order returned, and surface any breach in the push notification rather than letting it pass silently. The broker's order history is the only durable record — the execution container is ephemeral, so a breach that is not surfaced today is lost.

To analyze a ticker:

  1. Robinhood:get_equity_historicals → ~290 daily bars (closes). This is the input for indicators.py. Request a range that yields ≥220 bars (ideal for EMA200).
  2. Robinhood:get_equity_quotes → live price / last session close.
  3. If the user has a position: Robinhood:get_equity_positions (correct account) for size and P&L → set holding to correct value in scoring.

For the Macro-Sentiment pillar (once per session, shared):

  1. get_equity_historicals for the 8 ETFs: SPY, RSP, IWM, HYG, LQD, TLT, XLY, XLP.
  2. Attempt to fetch the 10Y-2Y yield spread from Investing.com (web) and inject it as yield_spread. If blocked by network egress policy or unavailable, omit it immediately without retrying: the script automatically redistributes its 20% weight among the other components and execution continues seamlessly without blocking.

For portfolio management:

  • Robinhood:get_portfolio → market value and buying power.
  • Robinhood:get_equity_positions → open positions by account.
  • Robinhood:get_realized_pnl → realized P&L (useful for the Friday review).

Computation Flow (Run via Code Execution)

Scripts are pure stdlib; they do not need internet access. They live in scripts/ inside this skill's own directory — the runtime gives me the base path when it loads the skill. I never hardcode that path: it differs between environments.

Robinhood historicals are large and routinely exceed the tool's output limit; when that happens the result is written to a file and I get the path back. I process them with code straight from that file — I never load raw bars into context.

Step 0 — append today's close (every session, before anything else). Daily bars from get_equity_historicals do NOT include the current session until well after the close: right after 16:00 ET the last bar is still yesterday, so scoring that series scores yesterday's market. For every symbol I take get_equity_quotes → last_trade_price (the ~19:59:59Z print is today's closing trade) and append it to the closes array with today's date, after asserting the last existing bar is the prior session. Never append last_non_reg_trade_price — extended-hours prints are not closes.

Step 1 — Macro (once per session). The input schema is {"as_of": "YYYY-MM-DD", "series": {"SPY": [...], "RSP": [...], …}, "yield_spread": <float, optional>}. The closes go nested under series, not at the top level — a flat {"SPY": [...]} raises ValueError: No components with sufficient data. Then run:

bash
python3 scripts/macro_pillar.py macro_input.json --json

Save the pillar_score (-2..+2). That number is the Macro-Sentiment score for ALL tickers today.

Step 2 — Per ticker. Assemble {symbol, close:[...], macro_score, holding} and run:

bash
python3 scripts/score.py ticker_input.json

This returns the three-pillar scorecard + decision (EXIT / TRIM, EXIT, RE-ENTRY (new cycle), TACTICAL REBOUND (counter-trend), HOLD (ride the cycle), HOLD (under review), WAIT (do not chase), STAY OUT / AVOID, HOLD / OBSERVE, OBSERVE) along with the exhaustion/bearish/rebound/death-cross flags that justify it. Passing the correct holding value is key: the decision cascade behaves differently depending on whether there is an open position or we are flat.

If only raw indicators are needed: python3 scripts/indicators.py ticker_input.json.

Three-Pillar Framework (Standard Output Format)

Each pillar ranges from -2 to +2:

  • Trend — EMA 20/50/200 structure + price position vs. EMAs + long-term slope.
  • Momentum — Wilder's RSI-14 + MACD histogram + TRIX-15 vs. signal.
  • Macro-Sentiment — from macro_pillar.py (cross-asset regime).

Report all three scores with their details, the total (-6..+6), and the decision framed in the logic of the Agentic account. Ruling principle: short-term returns via capital rotation — the cycle is enter on rebound → ride → exit on exhaustion → wait for next trigger. Accumulating positions is NOT the default (keeps capital trapped):

  • EXIT / TRIM when bullish momentum is EXHAUSTED (RSI turning from overbought, MACD histogram shrinking, price stretched / near upper Bollinger band).
  • EXIT when bearish momentum is RELENTLESS (true structural death-cross —EMA50<EMA200 and price<EMA50—, MACD histogram deepening, TRIX below zero).
  • RE-ENTRY (new cycle) when flat, when a rebound/reversal arrives with a healthy EMA structure: valid entry trigger, confirm with candle/volume.
  • TACTICAL REBOUND (counter-trend) when flat, when a rebound appears WITHIN a death-cross: a legitimate short-term opportunity, but with reduced size, close target (EMA20/EMA50 or middle Bollinger band), conditional exit on the next session / daily close if the rebound falters (since server-side stop orders are prohibited), and quick exit. It is not a new cycle and does not become a hold.
  • HOLD (ride the cycle) when holding a position with positive trend+momentum: maintain while watching for exhaustion; the next expected action is exit with profit, not adding to position.
  • HOLD (under review) when holding a position with weak structure or momentum, but no full exit trigger yet: maintain while monitoring for further deterioration.
  • WAIT (do not chase) when flat with a healthy trend but no fresh trigger: entering mid-trend has poor R/R; wait for pullback to EMA20 and turn.
  • STAY OUT / AVOID, HOLD / OBSERVE (when holding) or OBSERVE (when flat) as appropriate.

External Context (News + Analysts — Non-Blocking / Optional)

All external context (news, analyst ratings, yield spread) is strictly optional, best-effort, and non-blocking:

  1. News/macro: Investing.com (as defined in guardrails).
  2. Analyst ratings: Google Finance beta — https://www.google.com/finance/beta/quote/<TICKER>:<EXCHANGE>?tab=analysis Returns: consensus (Buy/Hold/Sell), 12m price targets (avg/max/min), analyst table with dates, and last earnings vs. estimates.
  3. Network egress policy & non-blocking execution: In remote scheduled runs, WebFetch to external sites (investing.com, google.com, cnbc.com, fred.stlouisfed.org, home.treasury.gov) is blocked by the network egress policy. Never let an external fetch error or egress block halt, delay, or fail execution. If external requests are blocked, time out, or return errors, skip them immediately without retrying and proceed purely with deterministic Robinhood data and local scripts. The macro pillar computes cleanly without the yield spread by redistributing its weight.
  4. If successfully fetched, report this as qualitative context alongside the three-pillar scorecard — it never modifies numeric scores or trading decisions. Highlight: consensus, average target vs. current price (upside or price already past target), and recent rating changes (<2 weeks).

Indicator Details (What the scripts calculate)

  • EMA seed = SMA of the first N bars (TradingView convention / adjust=False).
  • RSI-14 with Wilder's smoothing (not simple moving average).
  • MACD 12/26/9; report line, signal, histogram, and histogram slope.
  • TRIX-15 = % ROC of triple EMA, with EMA-9 signal.
  • Bollinger Bands 20/2 with population standard deviation; report %B.
  • Slopes are measured against 5 bars ago (configurable with --slope-lookback).

See scripts/indicators.py and scripts/score.py for exact implementation details. The math is verified against known test cases (constant EMA, monotonic series RSI, MACD = EMA12 - EMA26).

What This Skill Does NOT Do

It is not a signal service, and it is not a proven strategy: it is the user's framework executed with discipline. It runs on a schedule and executes on its own within the Mandate, but the framework has no backtest — a trigger firing does not make it correct. It does not average down. It does not touch protected positions. It does not trade options, crypto or margin. It does not generate HTML outside of Fridays.

© Oft3r, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 8 other files (scripts) in the repository root of Oft3r/agentic-trading-desk.

  • SKILL.md
  • .gitignore
  • LICENSE
  • README.md
  • gemini-spark-skill.zip
  • hooks/mandate-order-guard.sh
  • scripts/indicators.py
  • scripts/macro_pillar.py
  • scripts/score.py

Open the folder on GitHubat commit 908125f

Compare with similar skills

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Questions about Agentic Trading Desk

What does Agentic Trading Desk do?

Personal trading desk for short-term technical analysis on stocks/ETFs via Robinhood MCP. Agentic Trading Desk is an agent skill from Oft3r/agentic-trading-desk. Personal trading desk for short-term technical analysis on stocks/ETFs via Robinhood MCP.

When should I use Agentic Trading Desk?

Agentic Trading Desk fits situations like: the user asks to analyze a ticker; review positions; decide entries/exits/rebuys; calculate indicators (EMA/RSI/MACD/TRIX/Bollinger).

How do I install Agentic Trading Desk in Claude Code?

Run `npx skills add Oft3r/agentic-trading-desk --skill agentic-trading-desk -a claude-code`. Or copy the skill folder (the Oft3r/agentic-trading-desk repository) into .claude/skills/agentic-trading-desk in your project. Claude Code loads it when a task matches its description.

How do I install Agentic Trading Desk in Codex?

Run `npx skills add Oft3r/agentic-trading-desk --skill agentic-trading-desk -a codex`. Or copy the skill folder (the Oft3r/agentic-trading-desk repository) into .agents/skills/agentic-trading-desk in your project. Codex loads it when a task matches its description.

Can I use Agentic Trading Desk in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add Oft3r/agentic-trading-desk --skill agentic-trading-desk -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/agentic-trading-desk, .gemini/skills/agentic-trading-desk, .github/skills/agentic-trading-desk and .opencode/skills/agentic-trading-desk in your project.

What does Agentic Trading Desk need to run?

Going by SKILL.md and its folder, Agentic Trading Desk needs Python and a shell for the scripts in its folder and the command-line tools its instructions call (python3 and bash). Our summary lists: Python 3; A Bash shell.

Does Agentic Trading Desk access the network?

SKILL.md names 1 domain. In commands or code: google.com; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.

Is Agentic Trading Desk safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Agentic Trading Desk use?

Agentic Trading Desk is published under the MIT licence (from the LICENSE file in the skill folder). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Agentic Trading Desk use?

About 5.1k tokens (SKILL.md is roughly 20k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Agentic Trading Desk?

Skills that share tags, products or a category with Agentic Trading Desk: Tradingview MCP (atilaahmettaner/tradingview-mcp, 5k stars), Polymarket Tennis (livetennisapi/livetennisapi-mcp, 152 stars), Okx Sentiment Tracker (dex-original/okx-agent-trade-kit, 110 stars) and Tradingview MCP (himself65/finance-skills, 3.4k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Agentic Trading Desk?

Oft3r (a GitHub user) maintains it in Oft3r/agentic-trading-desk, which has 306 GitHub stars. The repository holds 2 skills in this directory. The repository was last updated on September 3, 2026.

Source: Oft3r/agentic-trading-desk on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.