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submit_batch_job

Submit batch jobs to download large historical market datasets for analysis, specifying symbols, date ranges, and output formats.

Instructions

Submit a batch data download job for large historical datasets

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
datasetYesDataset name (e.g., 'GLBX.MDP3')
symbolsYesComma-separated list of symbols
schemaYesData schema (e.g., 'trades', 'ohlcv-1m')
startYesStart date (YYYY-MM-DD or ISO 8601)
endYesEnd date (YYYY-MM-DD or ISO 8601)
encodingNoOutput encoding (default: 'dbn')dbn
compressionNoCompression type (default: 'zstd')zstd
split_durationNoSplit files by duration (default: 'day')day
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions 'submit a batch job' which implies an asynchronous, potentially long-running operation, but doesn't clarify whether this requires special permissions, what happens after submission (e.g., job status tracking via 'list_batch_jobs'), rate limits, or how results are accessed (likely via 'download_batch_files'). The description is insufficient for a mutation tool with no annotation coverage.

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 a single, efficient sentence with zero waste. It's appropriately sized and front-loaded with the core purpose, making it easy to scan and understand immediately.

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

Completeness2/5

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

For a tool that submits batch jobs (a mutation operation) with no annotations and no output schema, the description is incomplete. It doesn't explain what happens after submission, how to track job progress, where results are stored, or how to retrieve them. Given the sibling tools include 'list_batch_jobs', 'get_batch_job_files', and 'download_batch_files', the description should at least hint at this workflow.

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?

Schema description coverage is 100%, so the schema already documents all 8 parameters thoroughly with descriptions, enums, and defaults. The description adds no additional parameter semantics beyond what's in the schema, so it meets the baseline of 3 where the schema does the heavy lifting.

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

Purpose4/5

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

The description clearly states the action ('submit') and resource ('batch data download job for large historical datasets'), providing a specific verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like 'download_batch_files' or 'get_historical_data', which appear to be related but distinct operations.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives like 'download_batch_files' (which might retrieve already-generated files) or 'get_historical_data' (which might be for smaller, immediate queries). There's no mention of prerequisites, typical use cases, or when this batch approach is preferable to other methods.

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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