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SreeTarak2

DataFlow MCP Server

by SreeTarak2

get_contests_missing_images

Fetch contests where the primary image URL is missing or empty, identifying documents that require AI-generated replacement banners.

Instructions

Fetch contests where the primary image URL is missing or empty.

Use this to identify documents that need AI-generated replacement banners.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
skipNo
batch_sizeNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It communicates that the tool is read-only ('Fetch') and specifies the filter condition, which is helpful. However, it omits behavioral traits such as pagination semantics, how empty vs. null URLs are handled, and any performance implications from large result sets.

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 exactly two sentences. The first sentence states the core operation, and the second adds a purpose. Every word earns its place, with no filler or unnecessary detail.

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?

The tool is simple, and an output schema exists, so return values need not be described. The description covers the core purpose and differentiates from a close sibling. However, the complete absence of parameter semantics in both description and schema lowers completeness slightly, though the parameter names are reasonably self-explanatory.

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

Parameters2/5

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

Schema description coverage is 0%, and the description does not mention skip or batch_size at all. The parameter names are conventional, but no additional meaning is added in prose. Given the low schema coverage, the description should have compensated by explaining what these parameters control.

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 the specific verb 'Fetch' with the resource 'contests where the primary image URL is missing or empty,' which clearly states the exact condition. It also differentiates from the sibling tool get_contests_with_broken_images by specifying 'missing or empty' rather than 'broken.' The added purpose context ('identify documents that need AI-generated replacement banners') further clarifies intent.

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 explicitly states a use case: 'Use this to identify documents that need AI-generated replacement banners.' This gives clear context for when to select this tool. It does not explicitly mention alternatives or when not to use it, but the purpose statement is sufficient for an agent to understand when it applies.

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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