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glincker

glin-profanity-mcp

by glincker

compare_strictness

Compare profanity detection results across different strictness levels for the same text to see how sensitivity settings change flagged content.

Instructions

Compare detection results across different strictness levels

Input Schema

NameRequiredDescriptionDefault
textYesThe text to analyze

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.2

TDQS

B3.2/5.0
Behavior2/5

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

No annotations are provided, so the description must carry the full behavioral burden. It does not disclose whether the operation is read-only, what strictness levels are compared, what the response contains, or whether there are side effects such as storing the input text.

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 front-loaded sentence with no wasted words. It is appropriately sized for a simple one-parameter tool and immediately communicates the comparison focus.

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?

There is no output schema and no annotations, and the description does not explain what the comparison returns, which strictness levels are included, or how the results are structured. For a comparison tool, this leaves important context missing.

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?

Schema description coverage is 100% and the single parameter 'text' is documented in the schema as 'The text to analyze.' The description adds no parameter-level meaning beyond that, which is acceptable at the baseline for fully covered schemas.

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: 'Compare detection results across different strictness levels.' This is clear enough to understand the core operation, but it does not distinguish the tool from siblings like check_profanity or analyze_context, nor does it clarify what kind of detection is being compared.

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 phrase 'across different strictness levels' implies the tool is used when strictness comparison is needed, but there is no explicit when-to-use guidance, no exclusions, and no named alternatives. Usage is only inferred from the description.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.