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solver_schedule_optimization

Destructive

Optimize schedules by resolving conflicts and meeting constraints. Provide objectives and structured inputs to generate an efficient schedule.

Instructions

Run the solver domain agent action schedule_optimization.

Routes through the platform's domain-agent dispatcher under your JWT, tenant, and company scope.

Args: message: Free-text objective for the action. inputs: Optional JSON string of structured inputs for the action.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
inputsNo{}
messageNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.6/5.0
Behavior2/5

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

Annotations already flag this as destructive/non-read-only, so the description adds no meaningful behavioral context beyond that. It does not mention what side effects running the action may have, what gets changed, or any execution caveats.

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?

The description is compact and reasonably organized, with the action statement front-loaded followed by a short routing note and an Args list. It is not bloated, though the Args explanations are thin.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a solver action with destructive hints and no schema descriptions, the description should explain what scheduling optimization is used for and what types of inputs it expects. The presence of an output schema helps, but the missing domain context is a significant gap for an agent deciding whether to call this tool.

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 descriptions are absent, and the description provides minimal help by labeling `message` as a free-text objective and `inputs` as an optional JSON string of structured inputs. It does not explain what structured inputs are valid or what a good objective looks like.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific action (`schedule_optimization`) and identifies it as a solver domain-agent action, but it mostly restates the tool name without explaining what schedule optimization actually does for the user. It does not distinguish the tool from sibling solver tools like `solver_solve_optimization` or `solver_assign_resources`.

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?

There is no guidance on when to use this tool versus alternative solver tools or when the action is appropriate. The routing and scope information is context, not usable selection 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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