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Graph node details

get_graph_node
Read-only

Everything directly connected to one node, grouped by relationship: an entry's author/owner/source/ingredients/appliances/tools, an author's works, an ingredient's recipes, a user's collection. Exact and complete (unlike semantic search). Node ids are ':' — e.g. 'entry:' (prefix a search_recipes hit id with 'entry:'), 'ingredient:brown-sugar', 'author:mother-in-law', 'appliance:oven', 'user:'. User-supplied metadata is traversable too: 'tag:' (a shared free-form label) and 'property::' (a shared key=value, e.g. 'property:region:alaska') — every entry carrying that tag/value links to the same node. Recipes with named sub-preparations carry 'component::' nodes (HAS_COMPONENT from the entry; the component links to its own ingredients/steps) — e.g. "what else uses this sauce?" is one hop.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesGraph node id, or a bare recipe id from search_recipes (auto-prefixed with 'entry:').

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.7/5.0
Behavior5/5

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

Beyond the readOnlyHint annotation, the description discloses that results are exact and complete, returns are grouped by relationship, node IDs follow a type:key convention, bare search_recipes IDs are auto-prefixed with 'entry:', and metadata/component nodes are traversable. This is substantial non-obvious behavior that an agent needs to know.

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 long but every sentence carries necessary information, starting with purpose and exactness, then id syntax, then special node types. Examples are used instead of prose, and there is no filler or tautology.

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 description fully covers how to identify and invoke against a node, including unusual id types and auto-prefixing. Without an output schema, however, the exact response shape beyond 'grouped by relationship' is left somewhat implicit; pagination or limit behavior is also not mentioned. Minor gap.

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?

Although the schema already documents the single 'id' parameter at 100% coverage, the description adds concrete id formats and examples for entry, ingredient, author, appliance, user, tag, property, and component nodes. This goes well beyond the schema's one-line description and removes ambiguity about how to construct the parameter.

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 a precise action and resource: return everything directly connected to a single graph node, grouped by relationship type. The one-node scope and 'Exact and complete (unlike semantic search)' line separate it from siblings such as traverse_graph, find_graph_connection, and get_graph_overview without needing to open their schemas.

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 makes the intended use clear: when you need exact, complete one-hop graph relationships, and contrasts this with semantic search. It does not explicitly name alternatives like traverse_graph or provide when-not-to-use rules, but the examples ('what else uses this sauce?') give concrete invocation context.

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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