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mcp-lightcast

mcp-lightcast

by lawwu
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

Normalize Job Title

normalize_job_title
Read-onlyIdempotent

Normalizes raw job titles into standardized titles with confidence scores to support matching and analysis. Requires normalization permission and may use limited quota.

Instructions

Normalize a raw job title, with confidence. Requires normalization permission; may consume a limited quota.

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": {
      "title": "<title>"
    },
    "name": "normalize_job_title"
  }
}

Input Schema

NameRequiredDescriptionDefault
titleYes
versionNolatest

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.4.1

TDQS

B3/5.0
Behavior3/5

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

The annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false. The description adds useful operational context by stating that normalization permission is required and that the call may consume a limited quota, though it does not explain quota exhaustion or permission failure behavior.

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?

The description is a single front-loaded sentence with no wasted words. However, 'with confidence' is vague and could be more precise about what confidence refers to.

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 relatively simple, has an output schema, and the annotations cover safety traits. The description adds permission and quota context, but it is still incomplete regarding the version parameter and how this tool differs from sibling normalization tools.

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 carry parameter meaning. It implies the 'title' parameter through 'raw job title' but says nothing about the optional 'version' parameter or its default value 'latest,' leaving an important input undocumented.

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: 'Normalize a raw job title.' It does not explicitly distinguish this tool from sibling tools like normalize_title_and_extract_skills or normalize_title_and_get_skills, which also normalize titles but add skill extraction.

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?

There is no explicit guidance on when to use this tool versus the sibling normalize tools that also return skills. The phrase 'with confidence' implies a possible output characteristic but does not clarify selection criteria or alternatives.

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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