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aaronmsoto

finops-framework-mcp

by aaronmsoto

Get full text of a small framework entity

get_entity
Read-onlyIdempotent

Fetches full rendered markdown for FinOps entity types lacking dedicated tools, such as principles, phases, domains, technology categories, scopes, and personas.

Instructions

Full rendered markdown for entity types that have no dedicated tool. Required param: entity_type (principles | phases | domains | technology-categories | scopes | persona). Collections return whole (they are small); entity_type 'persona' also needs slug. For capabilities use get_capability; for KPIs get_kpis; for maturity levels get_maturity_model.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugNoRequired for entity_type 'persona'; ignored otherwise
entity_typeYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
uriYes
slugNo
markdownYes
entity_typeYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and openWorldHint=false, so the safety profile is covered. The description adds useful behavior beyond that: collections are returned whole because they are small, and persona additionally requires a slug. It doesn't discuss pagination or failure modes, but with annotations plus an output schema those are lower priority.

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?

Three tightly packed sentences that front-load the return type before stating requirements and alternatives. Slightly dense, but every clause carries information; no filler and no repetition.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With an output schema present, the return format need not be described, and the description covers everything else an agent needs: what is returned, the valid entity types, the required parameter, the persona special case, and the sibling routing. Nothing essential is missing for a two-parameter read tool.

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

Parameters4/5

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

Schema coverage is only 50% — the enum values carry no per-value documentation there — so the description earns its keep by listing all six valid entity_type values and specifying the conditional requirement of slug for 'persona'. That conditional logic is not present in the schema and materially affects a correct call.

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 states exactly what is returned (full rendered markdown) and scopes it to entity types that have no dedicated tool, enumerating them explicitly. It explicitly distinguishes itself from sibling tools by naming get_capability, get_kpis, and get_maturity_model as the correct routes for other entity types.

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

Usage Guidelines5/5

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

It gives both the when ('entity types that have no dedicated tool') and the when-not with concrete alternatives ('For capabilities use get_capability; for KPIs get_kpis; for maturity levels get_maturity_model'). The routing decision is fully determined without opening any schema.

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