pre-trade-check

name	pre-trade-check
description	Forced discipline gate before any discretionary buy or sell. Use BEFORE placing any trade - intraday, swing, or position. Triggers on "should I buy X?", "thinking about X", "going to enter X", "is now a good time for X?", "I want to buy X", "saw X on twitter", "X is ripping". Refuses approval when FOMO, sizing, or stop-discipline rules are violated.

Pre-Trade Check (Behavioral Guardrail)

Goal

Stop bad trades before they happen. This skill is a filter, not a recommender. Output is PASS or REJECT with reasons. Most retail losses come from emotional entries - this skill makes those entries explicit and refusable.

When to invoke

Any time the user is considering a buy or sell. Especially:

• Symbol seen on TikTok / X / Reddit / news
• "Friend told me about X"
• After a big up day on a name
• After a big down day on a held name (panic-sell candidate)
• Any FOMO / regret language

How to run

Step 0 - Establish intent (REQUIRED before any tool call):

If user has not stated, ask explicitly:

1. Ticker?
2. Direction? (BUY new / ADD existing / SELL / TRIM)
3. Horizon? (intraday / swing days-to-weeks / position 1-6mo / long-term)
4. Dollar amount considered?
5. Why now? (specific catalyst, technical setup, or "saw it on X")

If user can't answer #5 with a specific reason that isn't "saw it on social media" → output REJECT: no thesis and stop. Do not run other tools.

Step 1 - Pull state (parallel):

1. mcp__aifolimizer__get_profile - total capital, per-account cash
2. mcp__aifolimizer__get_portfolio - current holdings, weights, existing position in this ticker if any
3. mcp__aifolimizer__get_technicals with symbols=[TICKER]
4. mcp__aifolimizer__get_fundamentals with symbols=[TICKER]
5. mcp__aifolimizer__get_positioning_signals with symbols=[TICKER]
6. mcp__aifolimizer__get_news_headlines with symbols=[TICKER], limit=10
7. mcp__aifolimizer__get_live_track_record (no args) - user's own win-rate over last 30d
8. mcp__aifolimizer__get_ticker_decision_history with ticker=TICKER - prior decisions on this name
9. mcp__aifolimizer__get_personal_context (no args) - use derived.province + derived.marginal_tax_rate_pct to ground the non-reg short-term-gain warning in Rules. If present == false, state that warning as generic (no rate).

Step 2 - Run filter gates (in order, stop at first REJECT for fatal gates):

Fatal gates (any one fails → REJECT, stop)

Gate	Rule	Fail action
FOMO-rip filter	Daily change today > +5%, or 3-day change > +10%, AND reason was "saw on X / TikTok / news"	REJECT. State price and require 48h cooldown.
Crowding cap	crowding_score >= 75 for BUY/ADD	REJECT. State score and Goldman 2025 finding (consensus = negative expected alpha).
Position size sanity	Proposed $ > 5% of total portfolio for any single BUY/ADD	REJECT. State max allowed = 5% of total NAV.
No stop plan	User cannot answer "what price do I exit if wrong?"	REJECT. Compute ATR-based stop suggestion and require user confirm.
Concentration violation	Position post-trade would exceed 10% single-name or sector > 35%	REJECT. State current weight + post-trade weight.
Stage 4 add	Technical stage == 4 AND direction is BUY/ADD	REJECT. State "downtrend + below 200SMA - do not add to losers without fundamental override".
Recent stop-out re-entry	get_ticker_decision_history shows stop hit in last 30 days AND no new thesis	REJECT. List prior stop date + price. Require explicit new bullish catalyst.

Warning gates (do NOT block, but list in output)

Gate	Rule
RSI overbought	rsi_14 > 70 - entry late, expect pullback
Lottery/MAX spike	lottery_flag == true - abnormal single-day pop in last 21d (max_1d_return_21d_pct). Bali-Cakici-Whitelaw: high-MAX names underperform ~1%/mo. For BUY/ADD, treat as chase risk - wait for the spike to mean-revert before entry.
Below SMA50	Price < SMA50 - counter-trend entry
Earnings within 5 days	Per get_fundamentals.next_earnings - binary event risk
Negative news headlines	>50% of recent headlines negative tone
Personal track record poor	User's 30d win rate < 40% - cooling-off recommendation
Wide spread / low volume	volume_score < 0.5 - execution risk
Below-average ADX	adx_14 < 20 - chop regime, swing setups weak

Step 3 - Levels + sizing (only if all fatal gates PASS):

Call mcp__aifolimizer__get_trade_ticket with ticker=TICKER, action=<BUY|ADD|SELL|TRIM>, conviction=<HIGH|MED|LOW from thesis strength>. This is the single source of truth for levels - do NOT hand-roll them:

• entry_zone - {timing: buy_now | wait_pullback, low, high, reference, support_basis}. If timing == wait_pullback, the disciplined call is WAIT - state the pullback band + support basis; do not approve a market entry at current price.
• stop_loss_price - SMA20/ATR-anchored stop.
• exit_ladder - tiered [{label, price, sell_pct, gain_pct, rationale}]. Render verbatim; do not recompute targets.
• position block (only if already held) - avg_cost, return_pct, stop_below_cost.

Then apply risk-based sizing (the gate's discipline - OVERRIDES the tool's conviction-based size):

1. Risk per trade = 1.5% of total NAV (default; ask if user wants different).
2. Entry = entry_zone.reference.
3. Stop = stop_loss_price.
4. Risk per share = entry - stop.
5. Max shares = floor(risk_per_trade / risk_per_share).
6. Position $ = max_shares × entry; Position % = position_$ / total_NAV.
7. If position_% > 5%, cap shares so position = 5% of NAV (max-size rule wins).
8. Exits = exit_ladder (do not recompute).

Step 4 - Output decision card:

PRE-TRADE CHECK · <TICKER> · <DIRECTION> · <HORIZON>
================================================
Verdict: PASS / REJECT
Reason: <one line>

Fatal gates:  [✓] FOMO  [✓] Crowding  [✓] Sizing  [✓] Stop  [✓] Concentration  [✓] Stage  [✓] Re-entry
Warning gates: <list any that triggered>

If PASS, trade ticket:
  Entry:    zone $LOW-$HIGH  (<buy_now | WAIT pullback> · <support_basis>)
  Stop:     $X.XX (-A.A%)
  Exits:    T1 $.. (+b% sell 40%) · T2 $.. (+c% sell 35%) · T3 $.. (+d% sell 25%)
  Shares:   N   (risk-based: 1.5% NAV ÷ risk-per-share)
  Cost:     $C,CCC
  Position: P.P% of $NAV total
  Max loss: $L (risk = R.R% of NAV)
  Held:     avg $.. · ret +X% · stop below cost? Y/N   (omit line if not held)

Personal track record (30d):
  Win rate: X%
  Avg win:  $X    Avg loss: $X    R-multiple: X.XR
  Verdict:  <healthy / cooling-off recommended / suspend trading>

Next action: <log via log_recommendation if PASS, else nothing>

Step 5 - On PASS, log the intent:

Call mcp__aifolimizer__log_recommendation with:

• skill="pre-trade-check"
• ticker=<TICKER>
• action=<BUY/SELL>
• conviction="MED" (this skill is a discipline gate, not a conviction call - "MED" is the codebase's neutral default; log_recommendation only accepts HIGH/MED/LOW and raises ValueError on anything else)
• rationale=<user's thesis sentence>
• target_pct and stop_pct - the schema takes percentages from entry, not absolute prices. Compute from the ticket: let entry = entry_zone.reference, then stop_pct = (stop_loss_price - entry) / entry * 100 (negative for a BUY) and target_pct = (T2_price - entry) / entry * 100 (T2 = primary target from exit_ladder). Pass those two numbers. (log_recommendation has no entry_price/stop_loss/target_price args - passing them errors or silently drops the levels.)

This builds the forward track record for weekly-mirror skill.

Investor profile

• Always pull capital + accounts from get_profile - never hardcode
• Risk budget per trade: 1.5% of total NAV (ask user to override)
• Max single position: 5% of total NAV
• Max sector: 35% of total NAV

Rules

• Output ≤ 250 words including decision card
• Direct. "REJECT - crowding 82/100" not "you may want to reconsider given elevated positioning metrics"
• If user argues with a REJECT, do NOT flip. Restate the rule and ask them to wait 48h or change their thesis
• Never recommend a trade. This skill only rejects or passes. Picking is user's job
• ATR must be present - if atr_14 is null, REJECT with "insufficient data for risk-based stop"
• For SELL/TRIM direction: skip crowding gate, skip stage-4 gate. Apply: FOMO-panic filter (down day > -7% AND reason is "panic"), concentration unwind (good), tax-lot awareness (warn if short-term gain in non-reg, quoting derived.province + derived.marginal_tax_rate_pct from Step 1.9; if present == false, give the warning generically without a rate)

Gotchas

• get_live_track_record returns empty for new users - handle null gracefully, do not block on missing history
• crowding_score null for TSX (.TO) tickers - fall back to neutral, do not REJECT on null
• pivot_levels.s1 null for halted/new symbols - use current price as entry
• atr_14 requires ≥21 bars - REJECT IPOs and recently-listed tickers
• User-provided dollar amount overrides risk-based sizing only DOWNWARD (smaller is always allowed). If user wants larger than risk-based size, REJECT with the math
• "Friend's tip" / "X said" - counts as no thesis. REJECT at Step 0
• After REJECT, do NOT auto-rerun if user retypes. Require explicit "override" + written justification
• This skill is the user asking themselves to be disciplined. Honor that - do not soften output to be "nicer"