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SreeTarak2

DataFlow MCP Server

by SreeTarak2

submit_contest_details

Validate AI-generated contest details for quality and store them with automatic versioning.

Instructions

Submit AI-generated contest details (from Mistral) for validation and storage.

The details are validated for quality, then saved to the contest_details collection with automatic versioning.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
contest_idYesThe MongoDB ObjectId of the contest
details_jsonYesJSON string matching the contest-details-v1.0.txt schema

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

No annotations are provided, so the description carries the burden. It discloses that details are validated for quality, saved, and automatically versioned. It doesn't mention failure behavior, permissions, or idempotency, but the main workflow is transparent enough.

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?

Two concise sentences that front-load the purpose and then add essential workflow context. Every clause earns its place with no fluff or repetition of schema fields.

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

Completeness4/5

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

With an output schema present, return values are already covered. The description explains the validation, storage, and versioning enough for an agent to select and invoke the tool. It could mention integration with the generation flow (e.g., after get_contests_for_detail_generation), but that's not necessary.

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%, with both parameters explained in the schema. The description adds no additional parameter-level detail, but the baseline of 3 is appropriate since the schema does the heavy lifting.

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 uses a specific verb 'Submit' and clearly identifies the resource ('AI-generated contest details') and destination ('contest_details collection'). It distinguishes from sibling tools by specifying contest details rather than events or records.

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

Usage Guidelines4/5

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

The description provides clear context: this tool is for submitting AI-generated contest details for validation and storage. It doesn't explicitly name alternatives or exclusions, but the scope is obvious and it differentiates from sibling submission tools.

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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