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raimondasl

worldparts

by raimondasl

solve

Read-only

Determine the steady operating point of a water-handling system and retrieve measured values, component modes, warnings, and control loop states.

Instructions

Solve the steady operating point.

Returns the selected values with units (6 significant digits; pressures carry their reference, port pressures are bar gauge), the mode of every instance, component warnings and non-fatal pre-flight issues. Fails with the list of errors when check_system reports any. Controls: PI actuators are set to hold their setpoints, hysteresis switches hold their state; controls reports each loop (output, measured, setpoint, error, saturated or state).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
unitsNoUnit per path, e.g. {'v.volume_flow': 'L/s', 'mains.port.p': 'bar absolute'}; a key '*.<name>' matches every path ending in '.<name>'.
system_idYes
variablesNoPaths ('v.volume_flow', 'v.port_a.p'), instance names, 'control' or '*'. Default: observables, states, port pressures and control results.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
modesYes
issuesYes
valuesYes
controlsNo
warningsYes
convergedYes
system_idYes
iterationsYes
max_residualYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.2/5.0
Behavior5/5

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

Despite readOnlyHint=true, the description adds extensive behavioral detail: 6-significant-digit precision, pressure reference handling, port pressures in bar gauge, per-instance modes, component warnings and non-fatal issues, failure on check_system errors, and control loop behavior (PI setpoint holding, hysteresis state holding, and the `controls` report contents). This goes well beyond the annotations.

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 concise and well-structured: purpose sentence, return details, failure behavior, then control semantics. No sentence is wasted, and each clause contributes actionable information. Front-loading the core purpose makes it easy to parse.

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?

Together with the annotations (readOnlyHint) and the presence of an output schema, the description covers the key facts an agent needs: what the tool solves, what it returns, units and precision, failure condition, and control behavior. It omits only minor operational details such as convergence failure handling, which the output schema likely covers.

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?

With 67% schema description coverage, the schema already documents `units` and `variables` reasonably. The description adds meaning by explaining how selections are returned ('selected values') and by specifying unit formatting (significant digits, pressure reference/gauge), which clarifies the `units` parameter's effect. It does not elaborate on `system_id`, but that parameter is self-evident.

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 opens with a specific verb and resource — 'Solve the steady operating point' — and the output list (values, modes, warnings, errors) makes the scope concrete. This distinguishes it from siblings like simulate (transient) and solve_for (targeted solve) without needing to open their schemas.

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

Usage Guidelines2/5

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

No explicit guidance on when to use this tool versus simulate, solve_for, or check_system. The only contextual hint is 'Fails with the list of errors when check_system reports any', which describes failure behavior rather than recommending a workflow or specifying conditions for choosing this tool.

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