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backtest_strategy

Read-onlyIdempotent

Backtest a strategy on historical Solana OHLCV before deploying capital.

strategy_type is one of the 17 Crank strategy types (dca, momentum, rebalance, stoploss, protect, snipe, sentiment, vault, yield_farm, hedge, equity_dca, perp_grid, copy_wallet, market_make, arb, basis_trade, composite). asset is a token mint; timeframe one of 1m/5m/15m/1h/4h/1d; start_date/end_date are ISO-8601. params tunes the strategy (e.g. {"fast":5,"slow":20} for momentum). For strategy_type="composite" pass the signal-rule definition (see compose_strategy); the response includes a per-stream signal_coverage honesty report -- streams with partial persisted history are flagged, never silently zero-filled. slippage_model: "fixed" (slippage_bps haircut) or "jupiter_replay" (realised price-impact from the recorded quote corpus). Returns performance metrics (Sharpe/Sortino/Calmar, max drawdown, win rate, profit factor, VaR/CVaR), final equity, and trade + signal counts. Read-only simulation -- no fee, no on-chain action.

Workflow: SIMULATE step -- validate a strategy on history before risking capital; run twice (e.g. auto vs long_only) to compare. Poor Sharpe/deep drawdown -> retune or fall back to the yield leg. Feeds get_risk_assessment -> the strategy_*_create tools. See get_trading_workflow.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
assetYes
paramsNo
fee_bpsNo
end_dateYes
caller_idNo
timeframeYes
definitionNo
start_dateYes
slippage_bpsNo
strategy_typeYes
slippage_modelNofixed
wallet_addressNo
initial_capitalNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.8/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description discloses that the tool is read-only, simulates with no fees or on-chain actions, and provides honesty reports for composite strategies. This adds value beyond the annotations (readOnlyHint, destructiveHint) by detailing specific behavioral traits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with a clear purpose, parameter details, and workflow. It front-loads the main idea and contains useful examples. While slightly verbose in listing all 17 strategy types, it remains efficient overall.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (13 parameters, output schema exists), the description covers return metrics, honesty reports, slippage models, and workflow. It provides sufficient context for the agent to use the tool correctly without needing the output schema details.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage, the description compensates by explaining most parameters (strategy_type, asset, timeframe, dates, params, slippage_model, etc.) and their defaults. However, a few parameters like caller_id and wallet_address are not detailed, leaving minor gaps.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: backtesting a strategy on historical Solana OHLCV before deploying capital. It lists specific strategy types and differentiates this tool from siblings by positioning it as a simulation step.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit usage guidance: use before deploying capital, run twice for comparison, retune on poor Sharpe. It also references related tools (get_risk_assessment, strategy_*_create) and a workflow, giving clear when-to-use and fallback advice.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

B3.2/5.0
Disambiguation2/5

Multiple tools overlap significantly: close_perp_position vs perp_close, get_leaderboard vs get_score_leaderboard vs get_strategy_leaderboard, get_venue_status vs get_all_venues_status, send_token_social vs bulk_send_social, and get_crank_score vs get_score. Several read-only tools have nearly identical purposes, and the descriptions do not always clarify boundaries.

Naming Consistency4/5

Most tools follow a consistent verb_noun snake_case pattern (get_balances, create_strategy, set_alert, list_webhooks). However, there are deviations like 'lst_swap', 'jupiter_swap', 'flash_loan', 'sr_backtest', and the use of both 'get_' and 'list_' for reads, plus category prefixes like 'perp_' and 'strategy_' that vary in order. Overall still readable and predictable.

Tool Count1/5

177 tools is an extreme count for any server, far exceeding the 25+ threshold for 'too many'. Even a full DeFi platform does not need this many separate operations; the surface is overwhelming and clearly not well-scoped.

Completeness3/5

The domain (Solana DeFi trading) is covered extensively across swaps, perps, lending, staking, strategies, signals, and support. However, there are notable gaps: no lend_withdraw, no direct way to close a lending position, no spot order cancellation (though aggregator-based swaps may not need it), and a general lack of tiered account management. The huge number of tools makes it hard to identify missing lifecycle steps.

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