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framerudiments_visualisers

Lists installed renderer, sprite, and pinned visualiser capabilities, returning a retained background job to poll for results.

Instructions

List installed renderer, sprite or pinned visualiser capabilities. Returns a retained background job; poll danceflow_job_status. Base effect flags: none. Inspect danceflow_component for conditional inference/download effects.

Input Schema

NameRequiredDescriptionDefault
argumentsYes
permissionsNoAcknowledge only effects authorized for this operation; flags are not independent authority.

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.22

TDQS

A3.5/5.0
Behavior3/5

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

Beyond the annotations, it discloses the important async model ("Returns a retained background job") and the effect posture ("Base effect flags: none"), which explains why readOnlyHint is false despite a "list" verb. It still does not say what authorization the job creation needs, how long the retained job lives, or whether repeat calls are idempotent, so the disclosure is partial rather than complete.

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?

Four short sentences, front-loaded with the core action before the operational follow-ups. The telegraphic "Base effect flags: none" is slightly cryptic out of context but every sentence carries information; nothing is padded.

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 two-parameter tool with an output schema and full annotations, this covers the essentials: what is listed, that a job is returned, how to poll it, and the effect-flag posture. The only real gap is the absence of any differentiation from the renderers/sprites siblings, which matters given the dense sibling namespace.

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?

With 50% schema coverage and an empty `arguments` object, the description contributes by tying "Base effect flags: none" and the conditional inference/download effects to the `permissions` acknowledgment object, telling the agent it likely has nothing to declare by default. It adds no meaning for the required `arguments` parameter itself, which is undocumented in both places.

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 opens with a concrete verb and resource: "List installed renderer, sprite or pinned visualiser capabilities." That is more specific than the bare name, but it does not explain how this differs from the sibling tools framerudiments_renderers and framerudiments_sprites, whose subject matter it overlaps with in the same sentence.

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?

It gives real downstream routing — "poll danceflow_job_status" after calling and "Inspect danceflow_component for conditional inference/download effects" — which tells an agent what to do next. However, it never states when to choose this tool over framerudiments_renderers, framerudiments_sprites, or framerudiments_capabilities, so the selection decision against those siblings is left 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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