EmidLabs Backtest

Submit Confirmation Source

submit_confirmation_source

Runs a strategy against historical data purely to produce a signal timeline used to confirm OTHER backtests — not a backtest itself. Walks the same candles and evaluates the same DSL as submit_backtest, but never simulates a position: no trade, no PnL, no WinRate/drawdown, none of that applies here, because this strategy is never meant to be traded on its own. Returns immediately with an id and status — call get_confirmation_source to check completion, then pass that id as a confirmationSources sourceId in submit_backtest (e.g. only count an XRP entry once a BTC-neutral confirmation source agrees). Costs the same capacity as a regular backtest of the same size — the compute is identical, it just skips trade simulation.

Input Schema

TableJSON Schema

Name	Required	Description
`assetPair`	No	e.g. "BTC-USDC".
`finalDate`	No	ISO date string, e.g. "2025-06-01".
`initialDate`	No	ISO date string, e.g. "2025-01-01".
`backtestApiKey`	No	Your EmidLabs backtest API key (created in the Console). Not needed if this connector was added with a static 'x-api-key' header.
`backtestBaseUrl`	No	Defaults to the public production API. Override only for self-hosted/staging use.
`strategySnapshotJson`	No	The Strategy DSL object — identical shape to submit_backtest's own. riskManagement is accepted but never used (no position is ever opened), so it's fine to omit.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`id`	No
`status`	No

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

Changed1 schema field changedSep 2, 2026

addedInput schema / properties / strategySnapshotJson / properties / configuration / properties / timezone

Added value: +{
+  "description": "IANA timezone id (e.g. \"America/Sao_Paulo\") used to localize the DSL's hour()/minute()/dayOfWeek()/isWeekend() functions, for time-of-day or weekday gating conditions. Omit/null defaults to \"America/Sao_Paulo\".",
+  "type": [
+    "string",
+    "null"
+  ]
+}

AddedAug 31, 2026

TDQS

A4.7/5.0

Behavior5/5

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

The description discloses behavior well beyond the annotations: no trade, no PnL, no WinRate/drawdown, immediate return of id and status, and identical compute cost to a regular backtest despite skipping trade simulation. This gives the agent a clear mental model of side effects and cost. No contradiction with the annotations exists.

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 dense but every sentence adds non-obvious value: the confirmation-only purpose, the no-trade-simulation caveat, the async workflow with get_confirmation_source, and the cost equivalence. It is front-loaded with the most important distinction and avoids filler.

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?

For a tool with complex schema and an output schema, the description covers the full lifecycle: what it does, what it does not do, how to retrieve results, how to wire results into a subsequent backtest, and cost implications. An agent has enough context to invoke it correctly and understand the follow-up steps.

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

Parameters3/5

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

The input schema already covers 100% of parameters with rich descriptions, including the strategy DSL structure, so the description does not need to enumerate parameters. The tool description adds useful cross-context that the DSL matches submit_backtest's, but parameter-level meaning is otherwise left to the schema, which is sufficient.

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 opens with a specific, concrete statement: it 'runs a strategy against historical data purely to produce a signal timeline used to confirm OTHER backtests — not a backtest itself.' It clearly distinguishes this from submit_backtest by stating it never simulates a position, so an agent can understand exactly what this tool produces and how it differs from siblings.

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?

Usage guidance is explicit and actionable: call get_confirmation_source to check completion, then pass the returned id as a confirmationSources sourceId in submit_backtest. It also names the alternative submit_backtest and clarifies this tool is not for standalone trading, giving the agent both the workflow and the when-not-to-use signal.

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

A4.5/5.0

Disambiguation5/5

Each tool maps to a distinct resource and action: submitting/fetching backtests, fetching batch results, fetching trades, submitting/fetching confirmation sources, fetching signals, and listing available assets. The singular vs. batch result tools are explicitly cross-referenced and serve different call patterns, so an agent shouldn't confuse them.

Naming Consistency5/5

All tool names follow a consistent snake_case verb_noun pattern: submit_*, get_*, and list_*. Resource names are clear and predictable, such as backtest, backtest_batch, backtest_trades, confirmation_source, and confirmation_source_signals. The list_/get_ verb variation is conventional and not confusing.

Tool Count5/5

Nine tools is well-scoped for this domain, covering single and batch backtests, result and trade retrieval, asset discovery, and the confirmation-source workflow. Each tool has a distinct role, and none feel like filler or duplication.

Completeness5/5

The tool set covers the full backtesting lifecycle: submit single/batch, fetch aggregate results, fetch trade detail, list available assets, and submit/fetch confirmation sources plus their signals. The confirmation-source workflow integrates cleanly with submit_backtest, and there are no dead ends or obvious missing operations.

Resources

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