Skip to main content
Glama
rfalexandre
by rfalexandre

grafo_list_labels

Lists graph module labels and their schema properties to organize and query investigative data in the Pharus ecosystem.

Instructions

Lista labels do modulo de grafo, incluindo schema_propriedades.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
label_typeNo
label_codeNo
paginaNo
itens_por_paginaNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
serviceYes
operationYes
queryYes
summaryYes
paginationNo
dataNo
schema_hintYes
warningsNo
statusNook
errorNo
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states this is a list operation, implying it's likely read-only and non-destructive, but doesn't confirm this or mention any constraints like rate limits, authentication needs, or pagination behavior. The inclusion of 'schema_propriedades' hints at output content but lacks detail on format or structure.

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 a single, efficient sentence that directly states the tool's function without unnecessary words. It's appropriately sized and front-loaded, with every part contributing to the core purpose.

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?

Given the tool's complexity (4 parameters, no annotations, but with an output schema), the description is minimally adequate. It clarifies the resource and included data, but lacks parameter details and behavioral context. The presence of an output schema reduces the need to explain return values, but overall completeness is limited due to missing usage and parameter guidance.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate for undocumented parameters. It adds no information about the four parameters (label_type, label_code, pagina, itens_por_pagina), failing to explain their purposes, formats, or how they affect the listing. This leaves significant gaps in parameter understanding.

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?

The description clearly states the verb ('Lista') and resource ('labels do modulo de grafo'), making the purpose understandable. It adds specificity by mentioning 'schema_propriedades' as included content. However, it doesn't explicitly differentiate from sibling tools like 'grafo_list_graphs' or 'grafo_list_algorithms', which would require a 5.

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?

The description provides no guidance on when to use this tool versus alternatives. It doesn't mention any prerequisites, exclusions, or comparisons to sibling tools such as 'grafo_list_graphs' or 'grafo_list_algorithms', leaving the agent without context for selection.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/rfalexandre/pharus-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server