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Best crossbreeding layout from a pool of plant clones

genetics_best_layout
Read-onlyIdempotent

Best crossbreeding layout from a pool of plant clones. The gene calculator's beam search, ported exactly: which clones to plant around the centre, how many of each, and what the centre will most likely become (with every outcome's chance). Uses the game's gene weights (red W/X 1.0, green G/Y/H 0.6).

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "clones": "<clones>"
    },
    "name": "genetics_best_layout"
  }
}

Input Schema

NameRequiredDescriptionDefault
centreNoOptional genes of the plant in the centre slot (default: unknown).
clonesYesComma-separated 6-letter gene strings of the clones you have (G Y H W X).
targetNoOptional 6-letter target such as GGGGYY; default: as many G and Y as possible.
max_neighboursNoMost neighbouring plants to use (a planter grid allows 8).

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already cover safety (readOnly, idempotent, non-destructive, closed world). The description adds real substance beyond them: it names the underlying algorithm (beam search ported exactly), discloses the gene weighting scheme (red W/X 1.0, green G/Y/H 0.6), and states that every outcome's probability is returned.

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?

Two sentences with the purpose front-loaded and the output content trailing it; nothing is wasted. The gene-weight parenthetical is dense but earns its place by explaining the scoring model.

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?

With no output schema, the description carries the burden of explaining returns and does so ('which clones to plant around the centre, how many of each, and what the centre will most likely become, with every outcome's chance'). Combined with full schema coverage of the 4 parameters, an agent has enough to call it correctly.

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 description coverage is 100%, so the schema already explains centre, clones, target and max_neighbours in detail. The description adds no per-parameter syntax or format guidance beyond the schema; baseline 3 applies.

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?

The first sentence largely restates the title, but the second specifies the actual operation concretely: choosing which clones to plant around the centre, how many of each, and predicting the centre's outcome distribution. That distinguishes it in practice from genetics_predict, though no sibling is named outright.

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 'from a pool of plant clones' and the default target behaviour, but there is no explicit statement of when to call this instead of genetics_predict, nor any prerequisite or exclusion. The agent must infer the boundary.

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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