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generar_grafo_vinculos

Build a graph of corporate, political and judicial ties between people, companies and agencies, returning Mermaid and JSON link diagrams.

Instructions

Construye una red de vínculos societarios, políticos y judiciales entre personas, empresas y organismos, retornando código Mermaid y JSON.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
edgesYesLista de aristas: [{'source': 'ula', 'target': 'kimun', 'relation': 'traspaso $130M'}, ...]
nodesYesLista de nodos: [{'id': 'ula', 'label': 'U Lagos', 'category': 'sociedad'}, ...]
titleNoTítulo del diagrama de vínculos

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.5.1

TDQS

B3.2/5.0
Behavior3/5

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

No annotations are provided, so the description carries the burden. It does disclose the return artifacts (código Mermaid and JSON), which is genuinely useful given there is no output schema. However it says nothing about how nodes/edges are validated, error behavior, or size/scale limits.

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

Conciseness4/5

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

A single well-formed sentence with no filler; the resource and outputs are front-loaded. It is efficient, though it sacrifices some structure that could have carried usage guidance.

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?

For a graph-construction tool with no output schema and fully documented params, the description adequately conveys inputs (people, companies, organisms as nodes) and outputs (Mermaid and JSON). It is complete enough to invoke, with the main gap being behavioral/operational context rather than field-level detail.

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%, and the schema examples fully document the nodes and edges shapes plus the title field. The description only hints at node categories ('personas, empresas y organismos') and adds no syntax or format detail beyond the schema, so the baseline 3 holds.

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?

States a specific verb (Construye) and resource (red de vínculos societarios, políticos y judiciales entre personas, empresas y organismos), plus the output forms (Mermaid y JSON). This lets an agent understand the operation clearly, though it does not explicitly distinguish itself from the graphify_* siblings that also deal with relationship graphs.

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 on when to use this tool versus alternatives, nor any prerequisites or exclusions. The agent must infer its role purely from the verb and resource, with no routing advice toward or away from siblings like graphify_consulta_subgrafo.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.