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twining_add_relation

Add a relation linking two knowledge graph entities by specifying source, target, and relation type. Resolves entity IDs or names, reporting errors for ambiguous matches.

Instructions

Add a relation between two knowledge graph entities. Source and target can be entity IDs or names. Returns an error for ambiguous name matches.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sourceYesSource entity ID or name
targetYesTarget entity ID or name
typeYesRelation type: "depends_on", "implements", "decided_by", "affects", "tested_by", "calls", "imports", "related_to"
propertiesNoKey-value properties for this relation (max 50 entries, values ≤1000 chars)
Behavior3/5

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

No annotations are present, so the description must disclose behavior. It indicates a write operation and mentions error on ambiguous names, but lacks details on idempotency, permissions, or whether relations can be duplicated. Basic transparency with gaps.

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 efficient sentences, no wasted words. Information is front-loaded: purpose first, then specifics. Achieves clarity without verbosity.

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 main action and a key error case, but lacks information about return values (no output schema) and broader context like prerequisites or side effects. For a write tool, this leaves some gaps in completeness.

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

Parameters3/5

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

Schema description coverage is 100%, so the schema already explains all parameters. The description adds that source/target can be IDs or names and warns about ambiguous matches, which is mildly additive but not significantly beyond schema.

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 clearly states the tool adds a relation between two knowledge graph entities, with specific verb 'add' and resource 'relation'. It distinguishes from siblings like twining_add_entity (adds an entity) and twining_graph_query (reads) by its write operation on relations.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance on when to use this tool over alternatives. The description mentions error handling for ambiguous names but does not compare with sibling tools like twining_graph_query or twining_add_entity for similar tasks.

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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