Skip to main content
Glama
HorizunGroup

Horizun PBI MCP

by HorizunGroup

pbi_prepare_delivery

Run a pre-delivery audit on Power BI projects to produce a blocker checklist and apply automatic corrections. Compare quality scores before and after to ensure readiness.

Instructions

Checklist de pre-entrega con plan de correccion.

Audita el proyecto, produce un checklist de bloqueantes y propone las correcciones automaticas disponibles. Con dry_run=false las aplica y compara el puntaje antes y despues.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dry_runNo
request_idNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations, the description carries the full burden of behavioral disclosure. It transparently explains that with dry_run=true it only proposes corrections, and with dry_run=false it applies them and compares scores. This clearly signals the potential mutating behavior, which is critical for an agent 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 concise and front-loaded with the summary line 'Checklist de pre-entrega con plan de correccion.' It then provides necessary details in a compact two-sentence structure with no filler or redundancy.

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 covers the core workflow (audit, checklist, corrections, dry-run behavior) and since an output schema exists, return values are likely specified there. However, it lacks an explanation of request_id and does not detail what specific corrections or blockers are involved, leaving some context to be inferred.

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?

The description explicitly explains the dry_run parameter: 'Con dry_run=false las aplica y compara el puntaje antes y despues.' However, it does not mention the request_id parameter at all. Since schema coverage is 0%, the description partially compensates by explaining one of two parameters, but not the other.

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 tool's function: it audits the project, produces a blocker checklist, and proposes available automatic corrections. The term 'pre-entrega' gives specific context, but it does not explicitly differentiate from sibling audit tools like pbi_audit_project or pbi_plan_audit_fixes.

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?

Usage context is implied through 'Checklist de pre-entrega' (pre-delivery), suggesting when to use it. However, there is no explicit guidance on when to use this tool versus alternatives, nor any exclusions or prerequisites. The description lacks a clear 'use this when...' statement.

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/HorizunGroup/horizun-pbi-mcp'

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