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123Ergo

unphurl-mcp

show_defaults

Display the 23 scoring signals with default weights and descriptions to understand baseline scoring before creating custom profiles for URL intelligence.

Instructions

Show all 23 scoring signals with their default weights and descriptions. This is the baseline scoring that applies when no custom profile is specified.

Use this to understand what each signal means and how much it contributes to the score before creating custom profiles. Profiles are sparse overrides on top of these defaults.

This tool does not require an API key. The defaults are hardcoded and always available.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key traits: it's a read-only operation (implied by 'show'), requires no authentication ('does not require an API key'), and provides static data ('defaults are hardcoded and always available'). However, it doesn't mention potential rate limits or response format details.

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 efficiently structured in three sentences that each add value: the first states the purpose, the second provides usage guidance, and the third adds important behavioral context about authentication and data availability. There's no redundant information or wasted words.

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?

Given the tool's simplicity (zero parameters, no annotations, no output schema), the description provides complete context for understanding when and why to use it. It explains the relationship to sibling tools and the nature of the returned data. The only minor gap is the lack of output format details, but for a straightforward read operation, this is acceptable.

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?

The tool has zero parameters, and the schema description coverage is 100%. The description appropriately doesn't discuss parameters, maintaining focus on the tool's purpose and usage. A baseline of 4 is appropriate for a zero-parameter tool where the schema fully documents the empty input structure.

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 clearly states the tool's purpose: 'Show all 23 scoring signals with their default weights and descriptions.' It specifies the exact resource (scoring signals) and action (show with weights/descriptions), and distinguishes it from sibling tools like create_profile or list_profiles by emphasizing this is the baseline configuration.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description explicitly states when to use this tool: 'Use this to understand what each signal means and how much it contributes to the score before creating custom profiles.' It also clarifies the relationship to alternatives: 'Profiles are sparse overrides on top of these defaults,' indicating this tool should be used first to understand the baseline before using profile-related tools.

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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