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Mipiti
by Mipiti

Get Functional Coverage

get_functional_coverage

Retrieve a model's full functional coverage report: per-objective verified/covered/failing/untested states, Capabilities × Conditions matrix, and applicable/missing/non-applicable cell counts.

Instructions

Get the full functional coverage report for a model.

Read-only; no side effects. Returns per-objective state (verified / covered / failing / untested), the Capabilities × Conditions matrix, and the applicable / missing-objective / not-applicable cell accounting. This is the complete picture; when you only need the actionable subset (what to implement or fix next), use check_functional_gaps instead.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
model_idYesID of the threat model whose functional coverage to report.
server_versionYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.66.0
    • addedInput schema / properties / model_id / description
      Added value: +"ID of the threat model whose functional coverage to report."
  2. Addedv0.62.2
  3. Removedv0.62.0
  4. First observedv0.57.0

TDQS

A4.2/5.0
Behavior4/5

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

No annotations are present, so the description carries the full burden for safety-relevant behavior. It explicitly states 'Read-only; no side effects' and goes beyond the output schema by characterizing the report contents and its relationship to the actionable subset. This is strong behavioral context, though it does not cover topics like authentication or error behavior.

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?

Three concise sentences: purpose, safety and return contents, and sibling-tool routing. The most important information is front-loaded and no sentence is wasted.

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?

The output schema already covers return-value structure, and the description usefully describes the report scope and read-only nature. However, the required server_version parameter is left completely unexplained, which is a real gap for correct invocation. The rest of the context is strong, but this input ambiguity prevents a higher score.

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?

The input schema documents model_id, but server_version has no schema description and the tool description never mentions it. With only 50% schema coverage, the description needed to compensate for the undocumented required parameter, but it does not, leaving the agent without enough meaning to populate server_version confidently.

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 names a specific action ('Get'), a concrete resource ('full functional coverage report'), and a scope ('for a model'). It also signals that this is the complete picture, unlike the actionable subset, which distinguishes it clearly from sibling check_functional_gaps.

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 explicitly tells the agent when to prefer a different tool: 'when you only need the actionable subset ... use check_functional_gaps instead.' This gives a clear selection rule against at least one strongly related sibling and makes the intended use unambiguous.

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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