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Mipiti
by Mipiti

Get Design Leverage

get_design_leverage

Identify which design change removes the most critical and high-risk objectives from the threat model, so you can eliminate attacker positions by design before adding controls.

Instructions

Rank what eliminating each attacker position or asset BY DESIGN would remove from the matrix. Call this when deciding whether to change the design instead of implementing controls: it shows which single design change retires the most critical and high at-risk objectives. Read-only; no side effects.

Each row in ranked is an attacker or asset with the objectives its removal would take out of the matrix (objectives_removed, broken down by tier in removes), how many of those are currently at risk (removes_at_risk / removes_at_risk_by_tier), and the controls that would be retired. Rows are ranked by critical, then high, at-risk objectives removed. design_move (a concrete change of design that would eliminate the row) is filled only when include_design_moves is true. To act on a row, raise a design_change proposal with create_proposal; never apply a design change yourself.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topNoNumber of rows to return. Default 5.
model_idYesID of the threat model.
server_versionYes
include_design_movesNoAlso author a ``design_move`` per row. Default False.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.75.0

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations to inherit safety traits, the description carries the full burden, and it does well: it declares 'Read-only; no side effects,' explains the ranking order, discloses that design_move is populated only when include_design_moves is true, and describes the per-row fields. It does not cover edge cases such as empty results, tie-breaking, or failure behavior, which keeps it one step short of excellent.

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 rich but tightly organized: purpose, invocation context, output semantics, and the follow-up action rule each occupy clear, purposeful sentences. There is no filler, tautology, or unnecessary repetition, and the important 'never apply a design change yourself' rule is included without bloat.

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 read-only analytical tool with an output schema, the description supplies the call context, ranking semantics, row field meanings, and the required next step via create_proposal. It does not define the matrix or critical/high at-risk terminology, and server_version remains undocumented, but overall it is well above the minimum needed for an agent to select and invoke the tool correctly.

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 75%, so model_id, top, and include_design_moves are already documented in the schema. The description adds useful context by clarifying that design_move is filled only when include_design_moves is true, but it does not explain server_version or provide additional parameter-level detail beyond the schema, placing it at the baseline 3.

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 opening sentence states a specific action: ranking what eliminating each attacker position or asset BY DESIGN would remove from the matrix. It clearly distinguishes this from remediation-focused tools by framing the purpose as changing design instead of implementing controls, and it anchors the follow-up action to create_proposal.

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

Usage Guidelines4/5

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

The description explicitly tells the agent when to call it: 'Call this when deciding whether to change the design instead of implementing controls.' It also gives clear post-call guidance by instructing the agent to raise a design_change proposal and never apply a design change itself. However, it does not name sibling alternatives or state explicit when-not-to-use conditions, so it stops short of full exclusion guidance.

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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