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prismmoves_profile

Profile bounded local images and generate evidence-labelled JSON, HTML, Markdown, and SVG reports; returns a retained background job to poll for status.

Instructions

Profile bounded local images and write evidence-labelled JSON, HTML, Markdown and SVG reports. Returns a retained background job; poll danceflow_job_status. Base effect flags: write. 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

B3.4/5.0
Behavior4/5

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

Beyond the annotations, the description discloses that the tool writes reports, returns a retained background job, and requires polling danceflow_job_status. It also clarifies base write effects and points to danceflow_component for conditional inference/download effects, though it does not elaborate on output retention or authorization details.

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 description is short and front-loads the main purpose, report formats, and background-job behavior. The effect-flag sentences are terse but each contributes useful operational context.

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?

It covers the core workflow, async polling, and effect inspection, which is important for this complex tool. Still, for a nested schema with many configuration parameters, it omits substantial call-shaping information even though the annotations and output schema reduce some of the burden.

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?

The description only clearly maps to images and output, leaving role, device, models, lineage, max_edge, background, models_dir, pixelcue_url, allow_download, pixelcue_models, and permissions unexplained. With schema description coverage at 50% and a large nested arguments object, this does not compensate for the missing parameter semantics.

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 states a specific verb and resource: profile bounded local images and write evidence-labelled reports in named formats. It is clear but does not distinguish this tool from nearby image-analysis siblings such as pixelcue_visual_analysis or rastermoves_* tools.

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 post-call workflow guidance by saying to poll danceflow_job_status and to inspect danceflow_component for conditional inference/download effects. However, it does not state when to choose this tool over other image-profiling or visual-analysis siblings, nor does it give when-not-to-use conditions.

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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