list_rolesList the role taxonomy (title, slug, parent_slug). Use slugs as the role filter in search_jobs, job_trends, and salary_benchmarks.
This tool declares no required parameters. Add optional parameters from the input schema as needed.
{
"id": 1,
"jsonrpc": "2.0",
"method": "tools/call",
"params": {
"arguments": {},
"name": "list_roles"
}
}| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already establish readOnlyHint, idempotentHint, and destructiveHint. The description adds useful context by naming the exact output fields (title, slug, parent_slug) and indicating a hierarchical structure via parent_slug, which goes beyond the minimal safety profile. No contradictions or hidden side effects are disclosed, but the added field detail justifies a strong score.
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 extremely concise: two sentences, no redundant wording. The first sentence states the action and output fields; the second provides cross-tool usage guidance. Every word earns its place.
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?
For a zero-parameter, read-only listing tool without an output schema, the description is completely sufficient. It covers what fields will be returned and how to use them across sibling tools. No additional context is needed for an agent to invoke and leverage this tool correctly.
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 tool has no parameters, so the baseline is 4. The description correctly avoids discussing parameters since there are none, and the empty schema is fully covered. The focus on output semantics (role taxonomy) is the relevant semantic content here.
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 the tool's function: 'List the role taxonomy (title, slug, parent_slug)'. It uses a specific verb and resource, and distinguishes from siblings by focusing on role taxonomy rather than companies, jobs, or countries.
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 description gives explicit usage guidance: 'Use slugs as the role filter in search_jobs, job_trends, and salary_benchmarks'. This tells the agent not only what the tool does but how to apply its output in conjunction with sibling tools, clearly positioning it as a supporting look-up tool.
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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