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dMoERA Creator

by io.github.CacheCarti

submit_strategy

Submit a strategy for full validation and live deployment.

Runs the complete 7-stage validation pipeline:
1. static_check — code safety (banned imports, syntax)
2. in_sample — sanity check on training data
3. out_of_sample — test on unseen data (70/30 split)
4. walk_forward — rolling window validation
5. randomized_start — different random start points
6. perturbation — market stress test
7. holdout — server-side reserved data (pass/fail only)

If all stages pass, the strategy is registered for isolated live
paper trading with status="incubating". Promotion to "live" requires
a proven track record.

Args:
    name: Human-readable strategy name (e.g. "ETH Momentum v2").
    domain: Trading domain key (e.g. "eth_usdc").
    code: Python source code implementing the Strategy contract.
    user_id: The creator's user ID.
    symbol: Price symbol for historical data.

Returns JSON with: success, strategy_id, bot_id, validation results
per stage, or error details.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
codeYes
nameYes
domainYes
symbolNoETHUSDT
user_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

TDQS

A4.5/5.0
Behavior5/5

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

With no annotations provided, the description carries the full burden and does so thoroughly. It discloses the complete validation pipeline (including holdout being pass/fail only), the post-condition of status='incubating', and that promotion to live requires a proven track record. It also states the structure of the return JSON, including error details.

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

Conciseness5/5

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

The description is organized efficiently: purpose, numbered pipeline, post-conditions, argument list, and return format. Every section adds necessary information and the pipeline breakdown is valuable rather than fluff. It remains readable despite its length.

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 (7-stage pipeline, registration side effects, multiple parameters), the description is complete: it covers the validation process, success/failure outcomes, promotion path, parameter semantics, and return schema. The only mild gap, alternative tool selection, is already covered under usage guidelines. An agent has enough context to invoke it correctly.

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?

Schema description coverage is 0%, so the description must compensate and largely does. The Args section explains all five parameters with meaningful semantics: 'code' is described as 'Python source code implementing the Strategy contract', 'domain' gets an example, and 'symbol' is tied to historical data. It could go further with constraints or allowed values, but with no enums present it is solid.

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 states a specific verb and resource: 'Submit a strategy for full validation and live deployment.' It then enumerates the 7-stage validation pipeline, making it clear what the tool does and how it differs from simpler test or report tools. The mention of live paper trading adds further distinction from sibling tools.

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

Usage Guidelines3/5

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

The description implies when to use the tool (submitting a strategy for full validation and live deployment) but does not explicitly contrast with alternatives such as sandbox_backtest, which seems like the main alternative for testing without deployment. There are no exclusion criteria or when-not-to-use guidance, leaving routing decisions partially to inference.

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

A3.8/5.0
Disambiguation4/5

Most tools target a distinct resource and action, but browse_fund_marketplace and get_marketplace_bots are easy to confuse since both surface marketplace bots with performance metrics. The detailed descriptions clarify their different intents, though the naming does not strongly reinforce the distinction.

Naming Consistency4/5

The set almost uniformly uses snake_case verb_noun names like create_fund, list_funds, and update_fund_weights. Minor inconsistencies exist, such as get_marketplace_bots returning a list instead of a single item and browse_fund_marketplace using a different pattern from the other marketplace tools.

Tool Count3/5

At 26 tools, the server is on the heavy side and above the typical well-scoped range. The broad domain of funds, strategies, marketplaces, and market data helps justify the count, but several overlapping marketplace/list tools inflate the surface and could be consolidated.

Completeness4/5

The set covers the core fund lifecycle, roster management, strategy validation/deployment, marketplace browsing, and market data reads quite thoroughly. Minor gaps remain, such as no update/delete operations for strategies and no direct tool for publishing a bot to the marketplace, but these are workable within the existing workflow.

Resources