Jobs Related Skills
jobs_related_skillsReturn ranked related skills for a loaded skill trend.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| skill | Yes | Skill keyword, for example python. |
jobs_related_skillsReturn ranked related skills for a loaded skill trend.
| Name | Required | Description | Default |
|---|---|---|---|
| skill | Yes | Skill keyword, for example python. |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare read-only, idempotent, non-destructive behavior, so the description carries less burden. It adds useful context by stating that results are 'ranked' and that the operation depends on a 'loaded skill trend,' which goes beyond the schema and annotations. It does not describe the exact return structure, but the safety profile is already covered.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, focused sentence with no filler or redundant restatement of the tool name. The action ('Return'), result ('ranked related skills'), and scope ('loaded skill trend') are all front-loaded and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The definition is adequate for a simple, one-parameter, read-only tool, and the annotations cover safety. However, 'loaded skill trend' is never defined or linked to a prerequisite tool such as jobs_skill_trends, and with no output schema the ranking format and return shape are left to inference.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already documents the single 'skill' parameter with 100% coverage, including an example. The description adds some context by tying the input to a loaded skill trend, but it does not meaningfully clarify parameter format, constraints, or accepted values beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific verb ('Return') and object ('ranked related skills'), and scopes the operation to 'a loaded skill trend.' It is distinct from siblings like jobs_role_skills, but it does not explicitly name alternatives such as jobs_skill_graph or jobs_skill_trends, so differentiation is implicit rather than explicit.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'for a loaded skill trend' implies the tool is meant to be used after a skill trend has been loaded and when the agent needs related skills. However, it does not explain when not to use it, mention prerequisites, or point to comparable sibling tools such as jobs_skill_graph.
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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