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Save Monte Carlo settings

planitude_configure_simulation
DestructiveIdempotent

Turns the Monte Carlo simulation on or off for a project and saves its parameters (iterations, distribution, default range for tasks without a three-point estimate, seed), replacing the saved values. With the simulation on, the Risk tab of the web interface computes it automatically. Omitted fields keep their value. It does not move any date. Requires write permission.

Input Schema

NameRequiredDescriptionDefault
seedNoRandom seed for reproducible results.
enabledNoWhether the simulation is enabled for the project.
projectIdYesProject id (uuid), as returned by planitude_list_projects.
iterationsNoNumber of iterations.
distributionNoDuration distribution.
optimisticPctNoDefault optimistic range, percent below the duration.
pessimisticPctNoDefault pessimistic range, percent above the duration.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Goes well beyond the annotations by disclosing that saved values are replaced (consistent with destructiveHint=true), that omitted fields retain their current value (partial-update semantics), and that write permission is required. It also bounds side effects by stating no dates are moved.

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?

Front-loads the action and target, then layers scope, side effects, partial-update behavior, and prerequisites in four tight sentences with no wasted wording.

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 7-parameter mutation tool with no output schema, the description covers what changes, what stays, required permissions, and the absence of scheduling side effects. It does not say what defaults apply when enabling the simulation without supplying distribution or iteration values, a minor remaining gap.

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?

Schema coverage is 100%, so the baseline is 3, but the description adds real meaning by explaining that the optimistic/pessimistic range applies to tasks without a three-point estimate and by stating that omitted fields keep their value. It stops short of explaining how seed interacts with reproducibility at call time, which the schema already covers.

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?

States a specific verb+resource pair: turns the Monte Carlo simulation on/off for a project and saves its parameters, replacing existing values. It clearly differentiates from the sibling planitude_monte_carlo (compute) by framing this as persisting settings, and the title/description agree.

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?

Gives concrete context: enabling makes the Risk tab of the web interface compute the simulation automatically, and it explicitly notes a non-effect ("It does not move any date"). It does not name planitude_monte_carlo as the alternative for actually running/reading results, so routing guidance is implied rather than explicit.

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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