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/trader-memory-core

@e562af1

Track investment theses across their lifecycle — from screening idea to closed position with postmortem. Register theses from screener outputs, manage state transitions, attach position sizing, review due dates, and generate postmortem reports with P&L and MAE/MFE analysis. Trigger when user says "register thesis", "track this idea", "thesis status", "review due", "close position", "postmortem", or "trading journal".

Use this Skill: https://skilld.dev/gh/tradermonty/claude-trading-skills/trader-memory-core

This session only. Nothing lands on disk.

referencesfield_mapping.md

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Field Mapping: Source Skill → Thesis Canonical Fields

Mapping Table

Source Skill Raw Field Canonical Field Notes
kanchi-dividend-sop ticker ticker Direct
kanchi-dividend-sop buy_target_price entry.target_price
kanchi-dividend-sop current_yield_pct origin.raw_provenance.current_yield_pct Preserved in raw
kanchi-dividend-sop signal origin.raw_provenance.signal Preserved in raw
kanchi-dividend-sop verdict ingest eligibility Only CLEAN-PASS, PASS-CAUTION, or CONDITIONAL-PASS; all other or missing values fail closed
earnings-trade-analyzer symbol ticker Renamed
earnings-trade-analyzer grade origin.screening_grade A/B/C/D
earnings-trade-analyzer composite_score origin.screening_score 0-100
earnings-trade-analyzer gap_pct origin.raw_provenance.gap_pct Preserved in raw
earnings-trade-analyzer sector market_context.sector
vcp-screener symbol ticker Renamed
vcp-screener entry_ready origin.raw_provenance.entry_ready Boolean
vcp-screener distance_from_pivot_pct origin.raw_provenance.distance_from_pivot_pct
vcp-screener composite_score origin.screening_score
pead-screener symbol ticker Renamed
pead-screener entry_price entry.target_price
pead-screener stop_loss exit.stop_loss
pead-screener status origin.raw_provenance.pead_status SIGNAL_READY/BREAKOUT/etc
canslim-screener symbol ticker Renamed
canslim-screener rating origin.screening_grade
canslim-screener composite_score origin.screening_score
edge-candidate-agent id origin.raw_provenance.edge_id
edge-candidate-agent hypothesis_type origin.raw_provenance.hypothesis_type
edge-candidate-agent mechanism_tag mechanism_tag behavior/structure/uncertain
manual ticker ticker Required
manual thesis_statement thesis_statement Required
manual thesis_type thesis_type Required; must be a valid enum value
manual stop_price / stop_loss exit.stop_loss Optional
manual target_price / take_profit exit.take_profit Optional
manual entry_price origin.raw_provenance.entry_price Authoritative entry.actual_price set by open-position
manual entry_date origin.raw_provenance.entry_date Also drives _source_date (date-only [:10]) so the IDEA stamp is backdated
manual shares origin.raw_provenance.shares Fractional ok; authoritative position.shares set by open-position
manual setup_type setup_type Optional passthrough
manual (all other keys) origin.raw_provenance.* Preserved

Position Sizer (Update Operation, not Register)

Raw Field Canonical Field Notes
final_recommended_shares position.shares + position.shares_remaining shares_remaining seeded == shares
final_position_value position.position_value
final_risk_dollars position.risk_dollars
final_risk_pct position.risk_pct_of_account
mode — Must be "shares" (budget mode rejected)

position.shares is schema type number, exclusiveMinimum: 0 — fractional shares are valid (IBKR / Robinhood / IBI Smart / Alpaca etc.). Existing integer-share theses remain valid (number ⊇ integer).

Partial close (trim)

position.shares = the original opened quantity (immutable). position.shares_remaining (number, minimum: 0) = currently-open quantity. Each trim() and the final close write a status_history ledger entry:

Ledger field (status_history item) Meaning
shares_sold quantity sold in this leg
price execution price of this leg
proceeds round(price × shares_sold, 2)
realized_pnl round((price − entry_price) × shares_sold, 2)

outcome.pnl_dollars = Σ realized_pnl over all ledger entries; outcome.pnl_pct = pnl_dollars / (entry_price × original_shares) × 100. The ledger fields are optional in the schema, so legacy (non-trim) status_history entries stay valid; shares_remaining is optional too (absent ⇒ treated as fully open for legacy ACTIVE/CLOSED).

Manual Entry (free-form, non-screener)

The manual source ingests hand-entered positions. Input is free-form JSON — a single object or an array. Like every adapter it creates an IDEA thesis only; the authoritative entry price/date and (fractional) share count are set later by the open-position lifecycle step, not at ingest. entry_date is normalized to a date-only _source_date so the IDEA status_history entry is stamped at the entry date — keeping a backdated IDEA → ENTRY_READY → ACTIVE chain chronological.

Phase 1 Constraints

  • Single ticker only: Each thesis tracks exactly one stock symbol
  • edge-candidate-agent: Only tickets with research_only=False and a single ticker/symbol field are accepted. MARKET_BASKET or research_only tickets are skipped with a warning log.
  • pair-trade-screener and options-strategy-advisor are Phase 2 (multi-leg)

Raw Provenance

All adapter-specific fields not listed in the canonical mapping are preserved in origin.raw_provenance. This allows:

  1. No data loss during transformation
  2. Recovery of original values if canonical mapping changes
  3. Skill-specific analysis using raw data

Source: SKILL.md on GitHub

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  • Gen Agent Trust Hub4d

    The skill is a comprehensive trade journaling system for tracking investment ideas. It includes a CLI launcher, data ingestion adapters for various stock screeners, and a component for fetching price data from Financial Modeling Prep. It implements robust state management with atomic file writes and mandatory JSON Schema validation.

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Signed by skilld at e562af1. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.

Last checked against GitHub 17 hours ago.

Activeupdated 5 days ago

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