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szeider
by szeider

python_interrupt

Interrupt running code in the solving kernel while preserving its state. Use it to halt long-running MiniZinc solving without losing kernel progress.

Instructions

Interrupt running code in the solving kernel (state is preserved).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kernel_idNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv4.1.0

TDQS

B3.2/5.0
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 one meaningful trait — that state is preserved rather than discarded — but says nothing about what happens if nothing is running, whether interruption is cooperative, permissions, or the result of the call.

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; the verb and effect lead the reader immediately. It is efficient, though it is arguably too terse for the behavioral gaps it leaves.

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?

For a one-parameter tool with no output schema and no annotations, the description covers purpose and one behavioral note. It omits how to target a specific kernel and what the caller observes after interrupting, leaving the agent to guess at invocation details.

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?

One parameter (kernel_id, nullable, default null) has 0% schema description coverage, and the description adds no meaning: it never explains what kernel_id identifies, that it is optional, or what the default targets. The 'solving kernel' phrasing hints at a default target but is not tied to the parameter.

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?

States a specific verb ('interrupt') and resource ('running code in the solving kernel'), plus a scope qualifier ('state is preserved') that separates it from python_reset. It does not name siblings explicitly, so the differentiation is inferable rather than stated.

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 is implied by the verb: call it when running code needs to be stopped without losing kernel state. There is no explicit guidance on when to prefer this over python_reset, nor any prerequisite or condition (e.g., only valid while execution is in flight).

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