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blender_quality_guidelines

Read-onlyIdempotent

Fetch modelling quality guidelines covering real proportions, built structure, deliberate camera and lighting, and texture resolution to make generated 3D models believable.

Instructions

Fetch the modelling quality guidelines the agent should follow.

Covers the things that actually decide whether a generated model reads as believable: real proportions instead of convenient ones, built structure rather than modifier stacks, deliberate camera and lighting before a render, and texture resolution that survives a close-up.

Served from the server's own copy of the prompt. Asking the addon for it only worked when the addon happened to sit inside the source tree; from the installed location it could not resolve the package and silently returned a placeholder, so the agent got 200 characters of nothing useful.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
queryNoFree-text filter, e.g. 'wheels' or 'realism'.
response_formatNo'markdown' for readable output, 'json' for raw structured data.markdown

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv4.4.0

TDQS

B3.4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so safety is covered. The description adds that the content is served from the server's own copy rather than the addon, which usefully tells the agent the response is real content rather than the old placeholder. It does not describe filtering or output shape beyond the schema.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Purpose is front-loaded and the content overview is useful, but the final two sentences are largely historical narrative about the addon-package resolution bug. That provenance detail is interesting but occupies roughly a third of the text without helping an agent decide or invoke.

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 zero-required-param, read-only fetch with full annotation coverage and no output schema, the description is close to sufficient: it says what is returned and why it is trustworthy. It omits only the return format/pagination implications of the parameters, which the schema partially covers.

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?

The description adds nothing about the three parameters; 'wheels'/'realism' filtering, the limit, and the markdown/json choice are only in the schema. Schema coverage is a moderate 67% (limit and query have no descriptions), so the description neither compensates for the gap nor does real harm – baseline territory.

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?

States a specific verb and resource: 'Fetch the modelling quality guidelines the agent should follow.' The content summary (proportions, structure, camera/lighting, texture resolution) makes its scope concrete and it is clearly unlike any sibling. It stops short of naming an alternative, but nothing else in the toolset serves this resource.

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 only implied by 'the guidelines the agent should follow' and by references to 'before a render' and 'a close-up.' There is no explicit statement of when to invoke it versus related verification tools (e.g. blender_validate, blender_auto_validate) or whether it should be consulted before generating a model. Adequate but leaves sequencing to inference.

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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