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Generative AI Maturity Framework

get_maturity_level

Get one of the six maturity levels (1-6) with editorial content — hook, organizational reality, cross-dimension summary, common blockers to next level, worked industry example.

Input Schema

NameRequiredDescriptionDefault
levelYesMaturity level number, 1-6 (1=Aware, 2=Exploring, 3=Operational, 4=Integrated, 5=Autonomous, 6=Transformative).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
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 does disclose the return contents in useful detail (hook, organizational reality, cross-dimension summary, blockers, worked example), but says nothing about read-only nature explicitly, out-of-range handling for level values outside 1-6, or whether results are static content or personalized.

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 front-loaded sentence with no filler, and the resource scope leads. The em-dash list of five content types is dense but each item earns its place by telling the agent what to expect back.

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 one-parameter lookup with no output schema, the description covers what is returned, which is the main gap an agent would otherwise have. Nothing critical is missing, though a note on the level/dimension distinction would complete it.

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 coverage is 100% and the enum labels (1=Aware … 6=Transformative) are already in the schema; the description only restates the 1-6 range without adding format or selection guidance. Baseline 3 since the schema does the heavy lifting.

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 names a specific verb and resource ("Get one of the six maturity levels (1-6)") and enumerates the payload contents, so the agent knows this is an editorial lookup, not a raw data fetch. It never names a sibling such as get_dimension or get_framework_spec, so the boundary between a 'level' and a 'dimension' must be inferred.

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?

Use is only implied: the agent can conclude it should call this to retrieve a specific maturity level's editorial write-up. There is no statement of when to prefer this over get_dimension or get_framework_spec, and no prerequisites or exclusions are given.

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

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