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Picorn: search decorative areas

picorn_search_areas
Read-only

Find approved torn, wavy, blob, banner and other decorative shapes for a design.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
styleNo
aspectNo

TDQS

A3.7/5.0
Behavior4/5

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

The readOnlyHint annotation already declares this a safe read operation; the description adds the behavioral detail that results are 'approved' shapes, indicating a curated set. No contradictions.

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

Conciseness5/5

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

The description is a single sentence that immediately states the primary action and resource, with zero filler words.

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

Completeness2/5

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

While the core purpose is clear, the description omits any explanation of the three parameters, the meaning of 'approved', or the output format. With no output schema, the agent is left without sufficient context to construct effective queries.

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?

Schema description coverage is 0%, so the description must compensate. It provides examples of shape types (torn, wavy, blob, banner) that likely map to the 'style' parameter, but gives no guidance on 'limit' or 'aspect', leaving their semantics unexplained.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('Find') and names the resource ('approved torn, wavy, blob, banner and other decorative shapes'), clearly distinguishing it from sibling tools like picorn_search_icons.

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 description implies the tool is for retrieving decorative shapes for designs, but does not explicitly state when to use it over alternatives like picorn_search_icons, nor does it mention any exclusions or prerequisites.

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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TDQS

B3.4/5.0
Disambiguation5/5

Each tool targets a distinct resource or operation, with clear boundaries between image generation/editing and the many editor/video actions. Descriptions further clarify any potential overlap, making misselection unlikely.

Naming Consistency3/5

Most tools follow a verb_noun pattern, but the projects_* tools (create, inspect, update) reverse to noun_verb, and capabilities is a bare noun. This mixed convention is readable but not fully consistent.

Tool Count2/5

With 30 tools, the set exceeds the 25-tool threshold and feels heavy for an MCP server. While the broad scope justifies some size, many tools could be consolidated or split into focused servers.

Completeness3/5

Core image, editor, and video workflows are covered, but there are notable gaps such as no delete operations for editor/video projects, no update for video projects, and no lifecycle management for imported assets. These missing operations can create dead ends.

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