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fireostendere

DipTrace MCP

generate_placement_candidates

Generate deterministic placement candidates for selected components, respecting board constraints and keepouts. Returns candidate positions in millimeters for layout optimization.

Instructions

Generate bounded deterministic local placement candidates. All distances are in millimetres, regardless of the document's own Units attribute. Input schema: diptrace://schemas/tool-inputs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
gridNo
pathNo
regionNo
spacingNo
weightsNo
selectorYes
search_stepsNo
allowed_sidesNo
time_budget_msNo
respect_keepoutsNo
allowed_rotationsNo
deterministic_seedNo
board_edge_clearanceNo
max_candidates_per_componentNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

No annotations are provided, so the description carries the burden of behavioral disclosure. It does add useful traits: 'bounded deterministic' and the millimeter unit behavior regardless of document Units. However, it does not state whether the operation is read-only, what it returns (though output schema exists), or any side effects, leaving gaps.

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 two sentences, front-loaded with the core action, and includes a crucial unit caveat. Every sentence earns its place; the schema pointer is a minor addition but not wasteful. It is highly concise and well-structured.

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?

Given the tool's complexity (14 parameters, nested objects) and absence of annotations, the description is too sparse. It does not explain what placement candidates represent, how they relate to the component placement workflow, or what the output schema delivers beyond the candidate list. The output schema exists, but the description still lacks sufficient context for an agent to understand when and why to invoke this tool.

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?

Schema description coverage is 0%, and the description does not enumerate or explain any of the 14 parameters. It offers a global hint about distance units, which clarifies numeric parameters like grid and spacing, but leaves other parameters (weights, allowed_sides, deterministic_seed, etc.) without meaning. This fails to compensate for the schema's lack of descriptions.

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 uses a specific verb ('Generate') and resource ('bounded deterministic local placement candidates'), clearly distinguishing itself from sibling tools like analyze_placement or plan_component_placement. It conveys a precise action and scope without ambiguity.

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?

The description provides no guidance on when to use this tool versus alternatives, nor any exclusions or prerequisites. It is a bare action statement with no context about integration into placement workflows or relationships to other planning tools.

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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