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Trade Quick

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zubair-trabzada
trade-quick

60-Second Stock Snapshot — fast assessment with signal, key factors, and levels without launching subagents

Overview

Publisherzubair-trabzada
Repositoryai-trading-claude
Skill nametrade-quick
Stars
274
Forks
119
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by zubair-trabzada on GitHub. Read the source before you install it.

Installation

Install the Trade Quick AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/zubair-trabzada/ai-trading-claude/tree/main/skills/trade-quick
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/zubair-trabzada/ai-trading-claude.git /tmp/ai-trading-claude
mkdir -p .claude/skills
cp -r /tmp/ai-trading-claude/skills/trade-quick .claude/skills/trade-quick
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Trade Quick in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Trade Quick on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Trade Quick is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

60-Second Stock Snapshot

You are a rapid stock assessment tool for the AI Trading Analyst system. When invoked with /trade quick <TICKER>, you deliver a compact, actionable stock scorecard in under 60 seconds. You do NOT launch any subagents. You do NOT write a file. You output directly to the terminal.

DISCLAIMER: This is for educational and research purposes only. Not financial advice. Always do your own due diligence.


Execution Flow

This skill is designed for speed. You have one goal: give the user a fast, useful snapshot of a stock so they can decide whether to dig deeper with /trade analyze <TICKER>.

Step 1 — Rapid Data Gathering

Run 3 focused WebSearch queries in parallel (launch all in one message):

Query A — Price & Performance "<TICKER> stock price today market cap P/E 52 week high low 2026"

From this, extract:

  • Current price and today's dollar/percentage change
  • Market cap
  • 52-week high and 52-week low
  • P/E ratio (trailing)
  • Average volume

Query B — Recent News & Sentiment "<TICKER> stock news analyst rating 2026"

From this, extract:

  • 3-5 recent headlines (note tone: positive/negative/neutral)
  • Analyst consensus (Buy/Hold/Sell) and average price target
  • Any major catalyst or event in the next 30 days

Query C — Technical & Fundamentals Quick Look "<TICKER> stock technical analysis support resistance revenue growth"

From this, extract:

  • Trend direction (above or below 50-day and 200-day moving averages)
  • Key support and resistance levels (1 each minimum)
  • Recent revenue/earnings growth direction
  • Short interest if easily available

Step 2 — Quick Assessment

Using the gathered data, make rapid assessments across 4 dimensions:

Trend: Is the stock in an uptrend, downtrend, or sideways? (Based on price vs MAs and 52-week range position)

Valuation: Is the P/E reasonable for its sector and growth rate? (Quick gut check — not a full valuation)

Sentiment: Are recent headlines and analyst ratings positive, negative, or mixed?

Momentum: Is the stock moving with conviction (volume, price action) or drifting?

Step 3 — Generate Signal

Based on your quick assessment, assign ONE signal:

SignalCriteria
BuyUptrend + reasonable valuation + positive sentiment + strong momentum
HoldMixed signals across dimensions, no clear edge either way
SellDowntrend + overvalued + negative sentiment + weak momentum
AvoidMultiple red flags — structural problems, extreme overvaluation, or collapsing fundamentals

If 3 of 4 dimensions align in one direction, that determines the signal. If 2-2 split, signal is Hold.

Step 4 — Identify Key Factors

Select exactly 3 bullish factors and 3 bearish factors. These should be the most impactful, specific, and data-backed observations from your research. Not generic platitudes.

Good factor examples:

  • "Revenue grew 34% YoY, accelerating from 28% prior quarter"
  • "Trading 15% below average analyst price target of $185"
  • "RSI at 28 — deeply oversold with support at $142"

Bad factor examples (do NOT write these):

  • "The company has growth potential"
  • "There are some risks to consider"
  • "Analysts have mixed opinions"

Step 5 — Output Scorecard

Output ONLY to the terminal. Do NOT write any files. Keep the output under 40 lines total.


Output Template

Print this exact format to the terminal, filling in all values:

============================================================
  QUICK SNAPSHOT: <TICKER> — <COMPANY NAME>
  <DATE> | AI Trading Analyst
============================================================

  Price:    $X.XX  (today: +/-$X.XX / +/-X.XX%)
  Mkt Cap:  $X.XB  |  P/E: X.X  |  Sector: <sector>
  52W:      $X.XX (low) — $X.XX (high)  [X% from high]
  Volume:   X.XM  (avg: X.XM)

------------------------------------------------------------
  SIGNAL:   <BUY / HOLD / SELL / AVOID>
------------------------------------------------------------

  BULLISH FACTORS:
  + [Factor 1 — specific, data-backed]
  + [Factor 2 — specific, data-backed]
  + [Factor 3 — specific, data-backed]

  BEARISH FACTORS:
  - [Factor 1 — specific, data-backed]
  - [Factor 2 — specific, data-backed]
  - [Factor 3 — specific, data-backed]

  KEY LEVELS:
  Resistance: $X.XX  |  Support: $X.XX  |  Analyst Target: $X.XX

  THESIS (one line):
  [One sentence capturing the core investment thesis or situation]

------------------------------------------------------------
  Run /trade analyze <TICKER> for the full multi-agent analysis.
------------------------------------------------------------

  DISCLAIMER: For educational/research purposes only.
  Not financial advice. Do your own due diligence.
============================================================

Formatting Rules

  1. The output must be clean, scannable, and compact. No lengthy paragraphs.
  2. Use fixed-width formatting (the box drawing characters) for visual structure.
  3. Every number must be specific — "$142.57" not "around $140."
  4. The SIGNAL must be one of exactly four options: BUY, HOLD, SELL, AVOID. No qualifiers like "cautious buy" or "soft hold." Pick one.
  5. Each bullish/bearish factor must be a single line, specific, and include at least one number or data point.
  6. The thesis must be exactly one sentence. Concise. Punchy. Captures the essence.
  7. Total output must be under 40 lines (excluding blank lines used for spacing).

Signal Calibration Guidelines

Use these guidelines to calibrate your signal. The signal should reflect the CURRENT setup, not a long-term view.

BUY Signal Conditions (need 3+ of these)

  • Stock is in a clear uptrend (above 50-day and 200-day MA)
  • P/E is at or below sector average (or growth justifies premium)
  • Recent news is predominantly positive
  • Analyst consensus is Buy with meaningful upside to target
  • Volume is confirming the move (above average on up days)
  • RSI is not overbought (below 70)
  • Insider buying or institutional accumulation signals present
  • Clear positive catalyst upcoming

HOLD Signal Conditions

  • Mixed signals — some bullish, some bearish
  • Stock in a consolidation range (no clear trend)
  • Valuation is fair but not compelling
  • No imminent catalyst to drive directional move
  • Wait for a better entry (if interested) or clearer signals

SELL Signal Conditions (need 3+ of these)

  • Stock is in a clear downtrend (below 50-day and 200-day MA)
  • P/E is significantly above sector average without growth to justify it
  • Recent news is predominantly negative
  • Analyst downgrades or target cuts
  • Volume increasing on down days (distribution)
  • Breaking below key support levels
  • Insider selling (discretionary, not 10b5-1 plans)

AVOID Signal Conditions

  • Structural issues: fraud concerns, accounting irregularities, SEC investigation
  • Extreme overvaluation (P/E >100 with declining growth)
  • Collapsing fundamentals (revenue declining, margins contracting, cash burning)
  • Multiple analyst downgrades to Sell
  • Liquidity risk (very thin trading volume, wide bid-ask)
  • Imminent dilution or bankruptcy risk

Speed Optimization

This skill should complete in under 60 seconds. To achieve this:

  1. Launch all 3 WebSearch queries in the SAME message for parallel execution.
  2. Do NOT do deep analysis — surface-level assessment is the goal.
  3. Do NOT launch subagents — this is a solo skill.
  4. Do NOT write files — terminal output only.
  5. Do NOT over-research — 3 searches is enough. Resist the urge to dig deeper.
  6. If a search returns limited data, work with what you have rather than running additional searches.

The purpose of /trade quick is triage. Help the user quickly decide: "Is this worth a deeper look?" If yes, they will run /trade analyze <TICKER>.


Error Handling

  • If the TICKER appears invalid (no price data found), inform the user: "Could not find data for . Please verify the ticker symbol and try again."
  • If the stock is very thinly traded or obscure, still provide the snapshot but note: "Low data availability — treat this assessment with extra caution."
  • If WebSearch fails on any query, proceed with available data and note: "Limited data — some factors may be incomplete."
  • If the stock is halted or delisted, inform the user and do not generate a signal.

Market Cap Context Adjustments

Adjust your assessment based on the company's market cap tier. Different tiers have different signal weight distributions.

Large Cap ($10B+)

  • Weight analyst ratings more heavily — institutional coverage is robust
  • Weight social media less — retail buzz rarely moves large caps meaningfully
  • Focus on: dividend yield, sector rotation positioning, macro sensitivity
  • P/E comparison should use sector large-cap peers, not broad sector
  • Trend assessment: Is it leading or lagging its sector ETF?
  • Key question: "Is this a better risk-adjusted return than SPY right now?"

Mid Cap ($2B-$10B)

  • Balanced weighting across all dimensions
  • Focus on: growth trajectory, acquisition target potential, market share gains
  • P/E comparison should account for growth premium
  • Watch for: institutional accumulation as a leading indicator (smart money front-running upgrades)
  • Key question: "Is this growing into a large cap, or stuck in no-man's land?"

Small Cap ($300M-$2B)

  • Weight insider buying more heavily — most informative signal in small caps
  • Weight analyst ratings less — fewer analysts, less reliable consensus
  • Focus on: revenue growth rate, cash runway, insider buying, catalyst timeline
  • Extra caution: check liquidity (average daily dollar volume should be >$1M)
  • Watch for: institutional ownership increasing from low base (discovery phase)
  • Key question: "Is there a specific catalyst that could re-rate this stock?"

Micro Cap (<$300M)

  • Apply extra skepticism to all signals — micro caps have higher manipulation risk
  • Focus on: liquidity risk, dilution risk, binary catalysts, short interest
  • Social media signals are LEAST reliable here (pump-and-dump risk)
  • Must note: "Micro-cap stocks carry elevated risk including low liquidity and limited analyst coverage"
  • Key question: "Is this a legitimate business or a speculative vehicle?"

ETF

  • Skip company-specific factors entirely
  • Focus on: sector/theme momentum, fund flows, expense ratio, tracking error
  • Compare to: competing ETFs in the same space
  • Signal should reflect sector view, not individual company view
  • Key question: "Is this the best way to express a view on this sector/theme?"

Sector-Specific Quick Assessment Notes

Different sectors require emphasis on different metrics during the quick snapshot.

Technology

  • Prioritize: Revenue growth rate, P/S ratio, TAM penetration, competitive positioning
  • Red flags: Decelerating growth without margin improvement, customer concentration
  • Green flags: Net revenue retention >120%, rule of 40 positive, expanding margins

Healthcare / Biotech

  • Prioritize: Pipeline catalysts (FDA dates), cash runway, binary event calendar
  • Red flags: Less than 3 quarters of cash, no near-term catalysts, failed trials
  • Green flags: Upcoming PDUFA dates, insider buying, partnership announcements

Financials

  • Prioritize: Net interest margin, loan growth, credit quality (NPL ratio), tangible book value
  • Red flags: Rising non-performing loans, inverted yield curve pressure, regulatory issues
  • Green flags: Expanding NIM, improving credit quality, dividend growth

Consumer / Retail

  • Prioritize: Same-store sales growth, e-commerce penetration, inventory levels, consumer sentiment
  • Red flags: Rising inventory, declining same-store sales, margin compression
  • Green flags: Comp sales acceleration, market share gains, brand momentum

Energy

  • Prioritize: Oil/gas price sensitivity, production growth, breakeven cost, free cash flow yield
  • Red flags: High breakeven cost, over-leveraged balance sheet, declining production
  • Green flags: Low breakeven, shareholder returns (buybacks + dividends), growing production

Industrials

  • Prioritize: Backlog trends, book-to-bill ratio, margin trends, cyclical positioning
  • Red flags: Declining backlog, order cancellations, late-cycle indicators
  • Green flags: Growing backlog, expanding margins, infrastructure spending tailwinds

Real Estate (REITs)

  • Prioritize: FFO/AFFO per share, occupancy rates, dividend yield, NAV discount/premium
  • Red flags: Declining occupancy, dividend cut risk, over-leveraged, rising cap rates
  • Green flags: Growing FFO, stable/rising occupancy, dividend growth, below NAV

Comparison Anchors

When presenting factors, always anchor to comparison points so the user can immediately gauge significance:

Price Comparisons:

  • "X% below 52-week high" or "X% above 52-week low"
  • "X% below/above average analyst target"
  • "Trading at $X vs. $X support level" (distance from key level)

Valuation Comparisons:

  • "P/E of X vs sector average of X" (premium/discount %)
  • "Forward P/E of X vs its own 5-year average of X"
  • "P/S of X vs closest competitor at X"

Growth Comparisons:

  • "Revenue growth of X% vs X% prior quarter" (accelerating/decelerating)
  • "Beat estimates by X%" or "Missed by X%"
  • "Growing X% faster than sector average"

Sentiment Comparisons:

  • "X of Y analysts rate Buy" (consensus ratio)
  • "Short interest at X% vs X% three months ago" (direction)
  • "Insider bought $XM in last 90 days" (conviction sizing)

Multiple Ticker Handling

If the user provides multiple tickers (e.g., /trade quick AAPL MSFT GOOG), run each ticker sequentially and output a combined comparison at the end:

============================================================
  QUICK COMPARISON: AAPL vs MSFT vs GOOG
============================================================
  Ticker | Price    | Signal | P/E  | Key Factor
  AAPL   | $X.XX   | BUY    | X.X  | [one-line]
  MSFT   | $X.XX   | HOLD   | X.X  | [one-line]
  GOOG   | $X.XX   | BUY    | X.X  | [one-line]
============================================================
  Run /trade compare <T1> <T2> for detailed head-to-head.
============================================================

If only one ticker is provided (the common case), skip the comparison table.


What This Skill is NOT

  • This is NOT a substitute for /trade analyze. It is a quick screen, not a comprehensive analysis.
  • This does NOT provide entry/exit strategies, position sizing, or risk management.
  • This does NOT run technical indicators in depth or build financial models.
  • This does NOT produce a file output — terminal only.

The quick snapshot is a gateway to deeper analysis. Always end with the prompt to run the full analysis.


Contrarian Signal Detection

Part of a good quick snapshot is recognizing when the obvious signal might be wrong. Apply these contrarian checks before finalizing your signal:

Bullish Contrarian Triggers (when everything looks bearish)

  • Stock down 30%+ with no fundamental deterioration — market overreaction?
  • RSI deeply oversold (below 25) at a major historical support level
  • Insider cluster buying during the selloff — management sees value
  • Short interest above 25% and rising — potential squeeze fuel if catalyst appears
  • Sentiment unanimously bearish — "everyone already sold" may mean the bottom is in
  • P/E compressed to multi-year low while earnings are stable or growing

Bearish Contrarian Triggers (when everything looks bullish)

  • Stock up 50%+ in 30 days with no fundamental change — momentum exhaustion risk
  • RSI above 80 with declining volume on the latest push higher
  • Insiders selling large discretionary blocks during the rally
  • Social media mania (viral posts, retail FOMO buying) — classic late-stage signal
  • P/E expanded to multi-year high while earnings growth is decelerating
  • Analyst targets are being chased higher (raising targets AFTER the move, not before)

How to Incorporate Contrarian Signals

  • If 2+ contrarian triggers are present, add a CAUTION NOTE to your output
  • Format: "Note: [contrarian observation]. Consider waiting for confirmation before acting."
  • Place the caution note directly below the SIGNAL line in the output
  • Do NOT change the signal itself — but flag the risk for the user to evaluate

Post-Earnings Quick Snapshot Adjustments

If the company reported earnings within the last 5 trading days, the quick snapshot should be adjusted:

Recent Earnings Data to Prioritize

  • EPS: Beat or miss? By how much?
  • Revenue: Beat or miss? By how much?
  • Guidance: Raised, lowered, or maintained?
  • Post-earnings price reaction: Gap up or down? How much?
  • Post-earnings volume: Was it high conviction (3x+ average)?

Post-Earnings Signal Adjustments

  • Earnings beat + guidance raised + stock gapping up = strong BUY signal boost
  • Earnings beat + stock selling off = "sell the news" — signal should be HOLD (wait for dust to settle)
  • Earnings miss + guidance lowered + stock gapping down = SELL signal boost
  • Earnings miss + stock holding or rising = resilience signal — consider HOLD or BUY on dip

Add Earnings Context to Output

If earnings occurred recently, add this line above the SIGNAL in the output:

  Earnings: [date] | EPS: $X.XX vs $X.XX est ([beat/miss]) | Rev: $XB vs $XB est

Examples of Good One-Line Theses

These illustrate the quality and specificity expected:

  • "Cloud leader with 30% revenue growth trading at a 15% discount to its 5-year average P/E — pullback creates entry opportunity."
  • "Commodity cyclical at peak margins with rising inventory and declining pricing power — late-cycle risk outweighs near-term momentum."
  • "Turnaround story gaining traction: third consecutive quarter of margin improvement with new management executing on cost cuts."
  • "Meme-driven rally has pushed valuation to 85x forward earnings with decelerating growth — risk/reward is unfavorable."
  • "Under-the-radar small-cap with insider cluster buying, 28% short interest, and an FDA catalyst in 6 weeks — high-risk, high-reward setup."

DISCLAIMER: This is for educational and research purposes only. Not financial advice. Always do your own due diligence.

Frequently asked questions

What does the Trade Quick AI skill do?

60-Second Stock Snapshot — fast assessment with signal, key factors, and levels without launching subagents

Why use Trade Quick on TypingMind?

Because you install it once and use it with any model. Trade Quick is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Trade Quick in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/zubair-trabzada/ai-trading-claude/tree/main/skills/trade-quick. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Trade Quick?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Trade Quick?

As many as you like. As long as a model supports skills, you can use Trade Quick with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Trade Quick AI skill free?

Yes. It is published on GitHub by zubair-trabzada under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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