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Suggest pivots

suggest_pivots
Read-onlyIdempotent

For entity types found so far (a subdomain, an account, an email ...), the tools that take them as input, best first.

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": {
      "entity_types": "<entity_types>"
    },
    "name": "suggest_pivots"
  }
}

Input Schema

NameRequiredDescriptionDefault
entity_typesYesentity types, as list_types lists them

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint=false, and destructiveHint=false. The description adds that results are ordered 'best first', a meaningful behavioral detail beyond annotations, but it does not explain the ranking criteria or return format, so it only partially extends what the annotations provide.

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?

It is a single compact sentence with the input condition front-loaded and no filler. The fragment structure ('For entity types..., the tools...') is slightly less clear than a complete verb-led sentence, but the size is appropriate.

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 tool is simple with one required param and no output schema, and the description explains conceptually what is returned. However, it does not specify the return structure or ranking basis, nor does it mention alternatives, leaving some gaps for an agent that must consume and act on the suggestions.

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 100%, so the schema already defines entity_types and its constraint as list_types output. The description adds concrete examples (subdomain, account, email) and the 'found so far' context, giving meaning beyond the schema's minimal description.

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 identifies the input (entity types discovered) and the output (tools that accept them, ranked best first), which is a specific mapping task. It does not explicitly name the verb 'suggest' or state that it returns a ranked list, but the resource and scope are clear enough to distinguish it from list_types and search_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?

The phrase 'For entity types found so far' implies the tool should be used after entity types have been discovered, but it never states when to choose this over search_tools or list_types, nor any when-not conditions. Usage is implied rather than prescribed.

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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