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RationalBloks

by io.github.rationalbloks

Search Graph Nodes

search_graph_nodes
Read-onlyIdempotent

Search for nodes by property values in a deployed graph project.

Supports exact match and contains search (prefix value with ~ for contains).

Examples: Exact: filters: {"name": "Alan Turing"} Contains: filters: {"name": "~turing"} (case-insensitive) Combined: entity_type: "person", filters: {"field": "~physics"}

Without entity_type, searches ALL node types.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoMax results (default: 100, max: 1000)
offsetNoPagination offset (default: 0)
filtersYesProperty filters. Prefix value with ~ for contains search.
project_idYesProject ID (UUID)
entity_typeNoEntity key to filter by (optional — omit to search all types)
environmentNoEnvironment: staging or production (default: staging)

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare read-only, idempotent, and non-destructive behavior, so the description does not need to repeat safety. It adds valuable behavioral details: contains search via '~' prefix, case-insensitivity, and all-node-type search when entity_type is omitted.

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?

Description is compact and well-organized: one-line summary, a bullet for supported modes, and three concise examples. Every sentence earns its place, and the most important information appears early.

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 simple read-only nature and complete schema documentation, the description covers the key usage semantics. It does not describe the return shape, but no output schema is provided and the search behavior is the main concern; a short note on response format would elevate completeness, but the current state is adequate.

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

Parameters5/5

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

Schema coverage is 100%, yet the description adds meaningful interpretation beyond schema: examples for exact/contains filters, combined filter behavior, and the semantic of omitting entity_type. This is more than enough for an agent to construct valid queries.

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?

Description states the specific action ('Search for nodes by property values') and resource ('deployed graph project'). It clearly distinguishes from sibling tools like get_graph_node, list_graph_nodes, and fulltext_search_graph by emphasizing property-based search with exact/contains modes.

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?

Description provides concrete usage examples, including exact match, contains search, and combined filters, and explicitly explains behavior when entity_type is omitted. It does not explicitly name alternative tools or when not to use this tool, but the context is clear enough for most cases.

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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TDQS

A3.8/5.0
Disambiguation4/5

Most tools are clearly differentiated by domain (project vs graph_project) and action (create, get, list, delete). The main ambiguity is get_project vs get_project_info, which both claim to return detailed project information. Otherwise tool boundaries are clear.

Naming Consistency4/5

The server follows a strong verb_noun convention, with parallel naming for graph and non-graph tools (create_project/create_graph_project, deploy_staging/deploy_graph_staging). Minor deviations include bulk_create_graph_nodes and fulltext_search_graph, but patterns remain predictable.

Tool Count2/5

48 tools is a heavy surface, even when accounting for the two parallel product domains (relational and graph). Many tools are near-duplicates across domains, and the count exceeds the 25-tool threshold that feels manageable. It would benefit from consolidation or sub-servers.

Completeness4/5

Both project types have full life-cycle coverage: create, schema management, deployment, rollback, and deletion, plus graph data operations including bulk, search, and traversal. Minor gaps exist, such as no update_graph_relationship and the redundant get_project/get_project_info pair, but agents can accomplish core workflows.

Resources