Skip to main content
Glama

graphify_god_nodes

Identify the structural dogmatic pillars (God Nodes) of Chilean law via PageRank and centrality analysis on a doctrine and statute knowledge graph.

Instructions

Identifica los pilares dogmáticos estructurales (God Nodes) del sistema jurídico chileno según algoritmos de PageRank y centralidad sobre el Knowledge Graph de doctrina y normas.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
top_nNoCantidad de instituciones y normas principales a retornar (por defecto 10)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.5.1

TDQS

B3.3/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It usefully discloses that results are computed via PageRank/centrality over a knowledge graph (an analytical, implicitly read-only operation), but says nothing about cost/latency of a graph-wide algorithm, determinism, or error behavior for an empty graph.

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?

A single dense sentence with zero filler, front-loading the deliverable (God Nodes) before the method. Every clause contributes information, and the parenthetical gloss on the jargon aids interpretation.

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?

For a computation tool with no output schema, the description should hint at the return shape (ranked nodes, centrality scores). It implies a ranking of principal institutions/norms via top_n but never states the form of results, leaving a moderate gap.

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?

There is only one optional parameter (top_n) and the schema description coverage is 100%, so the schema already defines its meaning and default. The description adds no extra semantics beyond what the schema provides, making the baseline 3 correct.

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 ('Identifica') and a clearly named resource ('pilares dogmáticos estructurales / God Nodes del sistema jurídico chileno'), plus the method (PageRank y centralidad sobre el Knowledge Graph). An agent can distinguish this from graphify_analizar_impacto or graphify_explicar_institucion by the analytical concept, though no sibling is explicitly named.

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?

There is no when-to-use guidance, no prerequisites, and no reference to the other graphify_* siblings (consulta_subgrafo, trazar_camino, explicar_institucion, analizar_impacto). Usage must be inferred entirely from the general topic of graph analysis.

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