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case-studies

search_cases

Search DataArt case studies by text query and/or tag IDs with pagination. Pass an empty query to browse all cases. Use GetCaseTags to discover available tag IDs before filtering.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNoPage number, 1-based. Default is 1.
queryYesText to search in title and description. Pass empty string to skip text filtering.
tagIdsNoComma-separated tag IDs to filter by (e.g. "12,45"). Pass empty string to skip tag filtering.
pageSizeNoItems per page. Default is 20, maximum 50.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
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. It discloses pagination behavior and the browse-all mode, but does not describe the return format, error handling, or any side effects (e.g., whether it's read-only). For a search tool, read-only is implied, but the lack of any statement about response shape or potential limits is a gap. The description adds some value beyond the schema but not comprehensive behavioral context.

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 sentences with zero waste. The primary purpose is front-loaded, and the alternative usage (browse all) and sibling reference are woven in concisely. Every clause earns its place.

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?

Given the tool's simplicity (4 params, 1 required, no output schema), the description covers the key usage patterns and directs the agent to the sibling for tag discovery. It does not describe the return structure, but for a search tool the response is likely a list of case studies, which is reasonably inferable. The main missing element is a statement about what fields or format to expect in the response, but overall it is adequate.

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 coverage is 100%, so the baseline is 3. The description adds meaningful context by explaining the empty-query browsing pattern and pointing to GetCaseTags for tag IDs. This goes slightly beyond the schema's own parameter notes, which already mention skipping filters, but the description frames it as a user intent (browse all) and provides a discovery workflow. That extra guidance justifies a 4.

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?

States the specific verb 'Search', the resource 'DataArt case studies', and the filtering dimensions (text and/or tag IDs). It also explicitly mentions pagination, making the scope clear. It differentiates from the sibling tool by referencing GetCaseTags for tag discovery, so an agent can distinguish it immediately.

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?

Provides explicit guidance: 'Pass an empty query to browse all cases' gives a clear pattern, and 'Use GetCaseTags to discover available tag IDs before filtering' tells the agent exactly when to use the sibling tool. This is strong usage direction that leaves nothing 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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