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Cyoda-platform

Cyoda Calculation Node MCP

Official

search_search

Search entities using Cyoda-native conditions with group or simple field-value pairs for precise filtering.

Instructions

Search entities with Cyoda-native search conditions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
entity_modelYesThe type of entity to search (e.g., 'laureate', 'subscriber', 'job')
search_conditionsYesCyoda search condition structure: { "type": "group", "operator": "AND" | "OR", "conditions": [ { "type": "lifecycle", "field": "state", "operatorType": "EQUALS", "value": "VALIDATED" }, { "type": "simple", "jsonPath": "$.category", "operatorType": "EQUALS" | "CONTAINS" | "GREATER_THAN" | "LESS_THAN", "value": "physics" } ] } For backward compatibility, simple field-value pairs are also supported: {"field1": "value1", "field2": "value2"}
entity_versionNoThe entity model version (default: from config)1

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

With no annotations, the description must fully convey behavioral traits. It only says 'search', implying a read operation, but does not explicitly state that it is non-destructive, or disclose any other behaviors such as performance characteristics or required permissions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is very concise (one sentence), which is efficient but may be too brief to cover essential information like behavioral traits or usage context. It is front-loaded with the key action but lacks structure for complex details.

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

Completeness3/5

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

The description covers the input semantics well, but given the complexity of the search_conditions parameter and the presence of an output schema, it does not fully explain the tool's behavior, limitations, or return value structure. It is minimally adequate but incomplete for a sophisticated tool.

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?

The input schema has 100% description coverage, and the description adds significant value by detailing the Cyoda-native search condition structure, including example JSON and backward compatibility notes, which goes beyond the schema's property descriptions.

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 states it searches entities with Cyoda-native conditions, clearly indicating a search action on a specific resource. However, it does not differentiate from sibling tools like 'search_find_all' or 'entity_list_entities_tool', which also retrieve entities but with different methods.

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?

No guidance is provided on when to use this tool versus alternatives. The description does not mention prerequisites, context, or scenarios where other tools (e.g., 'search_find_all') would be more appropriate.

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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