AI Paper Trading Assistant for Crypto Research

Paper-first boundary

Trading Boy does not execute live trades, hold funds, or provide financial advice. This page is for simulated paper-trading review, prompt design, journal structure, and human review. It is not a signal feed, broker instruction, or promise of live trading results.

When to use this page

Use it when an agent should organize research context for paper review without recommending live trades.

A crypto research assistant is useful when the reviewer needs structure before a paper trade thesis exists. It can summarize context, name missing evidence, and prepare a journal handoff, but it should not turn every research note into a simulated entry.

Use the asset only after the paper-trading workflow, prompt version, permission boundary, and journal output format are clear. If the user cannot identify the setup, invalidation, risk field, or review question, the next action should be a skip, caveat, or human review rather than a confident simulated entry.

Crypto research assistant template

Review field	Pass condition	Paper-mode boundary
Research scope	Defines permitted sources, symbols, and timeframe.	The assistant cannot browse unrelated narratives mid-sample.
Context summary	Separates market structure, catalyst, liquidity, and uncertainty.	Context is evidence, not a signal.
Risk notes	Names volatility, correlation, data gaps, and paper sizing caveats.	Risk notes appear before the thesis.
No-key boundary	Does not require exchange keys for paper research.	Private account data stays out of the workflow.
Review handoff	Ends with questions for the trading journal or pre-trade checklist.	The assistant does not make the final decision.

Source-quality checks before a paper thesis

Crypto research can become noisy quickly. The assistant should make source quality visible before a reviewer decides whether the note deserves a paper-trading workflow.

Check	Useful evidence	Reason to skip
Timestamp	The source date, market session, and price context are visible.	The note mixes old news with current price action without saying so.
Market structure	The assistant separates trend, range, volatility, liquidity, and funding context.	The output treats a headline as a complete setup.
Watchlist fit	The symbol is already in the versioned paper watchlist or the reviewer records why it was added.	The assistant wanders into unrelated coins mid-sample.
Risk context	Volatility, correlation, stop distance, and paper size caveats are named before any thesis.	The note contains upside language but no invalidation or risk field.
Review handoff	The final row says research note, skip, paper thesis draft, or human review needed.	The output jumps straight from research into confident trade language.

Reusable prompt or worksheet text

Role: You are helping organize a simulated paper-trading review. You may summarize context, apply written rules, identify missing fields, and prepare journal evidence. You may not route live trades, request secrets, or provide financial advice.

Required output: Decision type, setup name, rule version, thesis, invalidation, paper risk, data caveat, behavior tag, and one human review question.

Skip rule: If setup, invalidation, paper risk, or data quality is missing, produce a skip or excluded row. Do not invent the missing field to make the record look complete.

Review handoff: Send the output to the paper journal, evaluation checklist, or human review checklist. Choose one next paper-mode action: collect more samples, tighten one field, pause, or revert a prompt change.

Example paper workflow

Scenario: The assistant summarizes BTC and ETH market context, flags a stale data source for one timeframe, and asks the reviewer whether the watchlist rule still applies. It does not say to buy or sell anything.

Good output: The research note makes uncertainty and missing data clear before any paper thesis is written.

Weak output: The assistant converts a news summary into a confident trade idea without risk context.

Decision: The reviewer keeps the evidence in paper mode, checks the output with the AI paper trading agent evaluation checklist, and records any prompt change in AI trading agent prompt versioning.

Use it with these controls

Prompt version: every sample should name the version that produced the output.
Output format: the agent should use consistent fields for entries, exits, skips, and missed setups.
Risk gate: size, exposure, drawdown, stop distance, and pause rules should be checked before judging the idea.
Human review: a person should approve prompt, risk, or workflow changes before the next sample.
Data privacy: private exchange credentials, account identifiers, and secret values should stay out of prompts and screenshots.

Where it fits in the paper-agent system

This page belongs before the trade thesis. Use it to organize context, expose uncertainty, and decide whether the next step is a skip, a paper thesis draft, or a human review.

After the research note is clean, move into the AI paper agent workflow, output format, risk controls, permission boundaries, and paper-trading limitations so the sample stays reviewable.

Research handoff examples

Research note only: A token has a catalyst, but the data source is stale and liquidity has changed. The assistant records the caveat and sends the item to human review instead of creating a paper setup.

Paper thesis draft: BTC is in a defined range, the watchlist version includes BTC, and the reviewer has a written invalidation rule. The assistant prepares a paper thesis draft for the AI paper trading agent evaluation checklist.

Skip: The source is social chatter, the symbol is outside the watchlist, and no risk field can be stated. The correct output is a skip with the missing evidence named.

Related AI paper-agent pages

Use these links to move between setup, output, risk, journal, and review pages without leaving the paper-first cluster.