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by ahmedak
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

slop_ignore

Stop slop detection for a phrase by marking it as acceptable. Apply the ignore rule to the current project or user-wide scope.

Instructions

Mark a phrase as NOT slop (e.g. domain jargon) so it stops being flagged.

Use when the user says a flagged phrase is actually fine in this context. scope='project' (this repo) or 'user' (machine-wide).

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "pattern": "<pattern>"
    },
    "name": "slop_ignore"
  }
}

Input Schema

NameRequiredDescriptionDefault
patternYes
scopeNoproject

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.2

TDQS

A4.1/5.0
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses the effect (stop flagging) and scope options, but doesn't detail persistence, reversibility, or what happens to existing flags. Adequate but not rich.

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?

Three sentences, front-loaded with the core purpose, no wasted words. Every sentence adds value.

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?

The description covers the core functionality and scope, but there is no output schema and no mention of return values or side effects. For a simple tool, this is acceptable but not complete.

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?

Schema coverage is 0%, but the description explains 'pattern' as the phrase to ignore and 'scope' as project or user with a default. This adds meaningful context beyond the schema's bare parameter names and types, though it could specify if pattern supports regex.

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 marks a phrase as NOT slop, distinguishing it from siblings slop_add (adds slop) and slop_detect (detects slop). The verb 'Mark' and resource 'phrase' are specific, and the purpose is unambiguous.

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

Usage Guidelines4/5

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

The description explicitly says 'Use when the user says a flagged phrase is actually fine in this context', providing clear usage guidance. It also explains the scope parameter. It lacks explicit when-not-to-use or direct comparison with siblings, but the context is clear enough.

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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