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Harrier

Harrier

by Caleb68864
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

generate_candidates

Generate ranked username and email candidates from a person's name parts to streamline intelligence collection.

Instructions

Generate ranked handle/email candidates from a person's name parts.

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": {
      "first": "<first>",
      "last": "<last>"
    },
    "name": "generate_candidates"
  }
}

Input Schema

NameRequiredDescriptionDefault
maxNo
lastYes
firstYes
maidenNo
marriedNo
nicknamesNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.1/5.0
Behavior2/5

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 mentions that candidates are 'ranked,' which is a useful trait, but it does not disclose whether the tool makes external calls, how ranking works, what inputs drive ranking, or any side effects. For a generate-only tool, more transparency about output behavior is needed.

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, focused sentence with no filler or repetition. It delivers the core purpose efficiently and is easy to parse.

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?

The tool has six parameters, including optional name parts and an array, and an output schema exists. The description is one sentence and does not explain how parameters like maiden or nicknames affect output, what ranking means, or how the output relates to downstream workflows. Despite having an output schema, the description leaves significant contextual gaps for an agent deciding to invoke this tool.

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 only generically refers to 'name parts,' which vaguely maps to first, last, maiden, married, and nicknames, but it does not explain the role of 'max,' 'maiden,' 'married,' or 'nicknames' in generating candidates. The description adds minimal meaning over the raw schema.

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 function: generating ranked handle/email candidates from person name parts. It uses a specific verb ('generate') and identifies the resource (handle/email candidates), distinguishing it from sibling tools like username_sweep or email_recon that likely perform checks or recon instead.

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

Usage Guidelines2/5

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

The description provides no explicit guidance on when to use this tool versus alternatives. It does not mention prerequisites, exclusion criteria, or how it relates to sibling tools like username_sweep or email_recon. The context 'from a person's name parts' implies usage but does not say when to choose this over other 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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