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Glama
Crazay247

autocad-arch-mcp

by Crazay247

hama_gold

Retrieves top construction exemplars and scores current CAD drawings against gold-standard criteria, enabling quality assessment and improvement.

Instructions

Hama gold teaching — every-run retrieval of construction perfection.

operations:

  • retrieve: data {intent: str, k: int=3} -> top-k gold exemplars (BARAL municipal + Hama A001/A020) via cosine similarity

  • similarity: data {features: dict, gold_id: str="hama_A001"} -> 0-100 vs Hama

  • extract: data {} -> extract current drawing features via ezdxf (layers, dims, hatches, viewports) for scoring

  • score: data {features: dict} -> composite Hama 0.5validator +0.3vision+0.2*sim

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataNo
operationYes
include_screenshotNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

A3.7/5.0
Behavior4/5

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

With no safety annotations beyond a title, the description carries the full transparency burden. It discloses meaningful behavior: the scoring formula (0.5*validator + 0.3*vision + 0.2*sim), the 0-100 similarity scale, the extraction method via ezdxf, and the specific gold exemplar sources. It does not mention permissions, side effects, or external dependencies, but the disclosed details are substantive.

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 bullet-list format is compact and scannable, with each operation showing inputs and outputs. The opening phrase 'Hama gold teaching — every-run retrieval of construction perfection' is semantically fluffy, but the rest earns its place by packing useful signatures into a small space.

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

Completeness3/5

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

The description is adequate for a multi-operation tool and an output schema exists, so return-value details are not needed. However, it leaves include_screenshot unexplained, assumes domain knowledge ('BARAL municipal', 'validator', 'vision', 'sim'), and never clarifies how the top-level operation parameter maps to the listed operation names. These are notable gaps for an agent selecting and invoking the tool.

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 description coverage is 0%, so the description must compensate—and it largely does. It explains the operation values and the expected data payload shapes for each operation, including intent, k, features, and gold_id. The only schema parameter it leaves undocumented is include_screenshot.

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 description clearly enumerates the tool's operations—retrieve, similarity, extract, score—each with a specific verb and target resource. It goes well beyond a tautology and gives a concrete sense of what the tool does. However, it does not contrast itself with sibling tools or explain the vague opening phrase 'every-run retrieval of construction perfection'.

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?

The operation bullets imply when to use each sub-operation (e.g., retrieve for exemplars, score for scoring), so there is some usage guidance. But the description never explicitly says when to choose hama_gold over its many nbc_* siblings, nor does it provide exclusion conditions or alternatives.

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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