Job descriptions, skills, education requirements, and wage data
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Average 4.4/5 across 4 of 4 tools scored.
Each tool targets a distinct aspect of occupational data: search, details, wages, and outlook. There is no overlap in purpose; even the three 'get_' tools are clearly differentiated by the data they return.
All tool names follow a consistent verb_noun pattern: 'search_occupations' and 'get_' prefixed tools. The verbs are clear and the nouns describe the resource or data type, making the pattern predictable.
With exactly 4 tools, the set is well-scoped for an occupational data server. Each tool serves a core need, and there is no redundancy or bloat.
The tool surface covers the full lifecycle of occupational data exploration: search to find occupations, then retrieve details, wages, and outlook. No obvious missing operations for the stated purpose.
get_career_outlookAInspectGet employment projections and career outlook for an O*NET occupation.
Returns projected job growth rate, employment numbers, projected openings,
and an outlook summary (bright, average, or below average).
Args:
soc_code: The O*NET-SOC code (e.g. '15-1252.00' for Software Developers).
| Name | Required | Description | Default |
|---|---|---|---|
| soc_code | Yes |
| Name | Required | Description |
|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses the return values and specifies the input format with an example. However, it does not mention potential errors, data source, or any edge cases. For a read-only lookup, this is fairly transparent but not exhaustive.
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 concise, front-loaded with the main purpose, and structured with a clear Returns section and Args. Every sentence adds necessary information, with no wasted words.
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 tool is simple with one parameter and an output schema (not shown). The description covers the return values and parameter format, making it complete enough for an agent to invoke correctly. It lacks some context about edge cases or when data might be unavailable, but overall sufficient.
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?
Schema description coverage is 0%, so the description must compensate. It provides a detailed explanation of soc_code, including the format (O*NET-SOC code) and a concrete example, which fully clarifies the parameter's meaning.
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 purpose: to get employment projections and career outlook for an O*NET occupation. It lists specific return values (job growth rate, employment numbers, projected openings, outlook summary), which distinguishes it from sibling tools like get_occupation_wages (wages) or search_occupations (search).
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 implies usage for when career outlook data is needed but does not explicitly mention when to use this tool instead of the siblings. It lacks alternative guidance or exclusion criteria, making it minimally adequate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_occupation_detailAInspectGet detailed information about an O*NET occupation.
Returns comprehensive data including description, skills, knowledge areas,
abilities, work activities, technology skills, and education requirements.
Args:
soc_code: The O*NET-SOC code (e.g. '15-1252.00' for Software Developers,
'29-1141.00' for Registered Nurses).
| Name | Required | Description | Default |
|---|---|---|---|
| soc_code | Yes |
| Name | Required | Description |
|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It clearly lists what data will be returned, but it does not explicitly mention that this is a read-only operation, nor does it disclose any potential errors, permission requirements, or limitations. The getter semantics are implied but not stated.
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 concise and well-structured: an opening purpose statement, a sentence enumerating returned content categories, and an Args block with parameter details. Every sentence earns its place with no redundancy.
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?
Given the tool's simplicity (one parameter) and the existence of an output schema, the description is sufficiently complete. It covers the essential input semantics and high-level return content. It could additionally note that invalid codes may cause errors or that search_occupations can help locate codes, but these are minor gaps.
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 input schema provides no description for soc_code (0% coverage). The description fully compensates by explaining the parameter meaning, giving the format, and providing real-world examples like '15-1252.00' for Software Developers and '29-1141.00' for Registered Nurses, making the parameter usage unambiguous.
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 purpose with a specific verb and resource: 'Get detailed information about an O*NET occupation.' It distinguishes itself from siblings like get_career_outlook and get_occupation_wages by focusing on comprehensive occupation detail rather than specific facets.
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 implies usage when comprehensive occupation data is needed, but it does not explicitly discuss when to use alternatives such as search_occupations for finding codes or get_occupation_wages for salary data. No exclusions or comparisons are provided, so the guidance remains implied rather than direct.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_occupation_wagesAInspectGet wage and salary estimates for an O*NET occupation.
Returns median, 10th, 25th, 75th, and 90th percentile wages,
both hourly and annual. Can be filtered by location.
Args:
soc_code: The O*NET-SOC code (e.g. '15-1252.00' for Software Developers).
location: Optional location filter — state name or 'National' (default: national).
| Name | Required | Description | Default |
|---|---|---|---|
| location | No | ||
| soc_code | Yes |
| Name | Required | Description |
|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden. It transparently discloses the exact percentiles returned (median, 10th, 25th, 75th, 90th), both hourly and annual, and explains the location filter with a default of national. This is good for a read-only tool.
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 concise, well-structured, and front-loaded with the main purpose. The args list is clear and every sentence provides useful information without redundancy.
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 simple tool with two parameters and an output schema, the description covers all essential aspects: what data is returned, the filtering capability, and parameter semantics. There are no significant gaps.
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?
Schema coverage is 0%, but the description fully compensates by explaining both parameters: soc_code with an example format, and location with accepted values ('state name or National') and default behavior. This adds significant meaning beyond the bare schema.
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 gets wage and salary estimates for an O*NET occupation, using a specific verb and resource. It differentiates from sibling tools like get_career_outlook (outlook data) and get_occupation_detail (details).
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 implies the tool is for retrieving wage data, but it does not explicitly state when to use it over alternatives or provide exclusions. For example, it doesn't mention 'Use this for wage estimates, not for career outlook.'
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
search_occupationsAInspectSearch O*NET occupations by keyword.
Returns a list of occupations matching the keyword with their SOC codes,
titles, and relevance scores. Use the SOC code from results with other
O*NET tools to get detailed information.
Args:
keyword: Search term (e.g. 'software developer', 'nurse', 'electrician').
limit: Maximum number of results to return (default 25).
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| keyword | Yes |
| Name | Required | Description |
|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses the return format (SOC codes, titles, relevance scores) and the integration point. It doesn't mention edge cases like empty results or pagination, but for a read-only search tool this is adequate.
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 compact, front-loaded with the purpose, and structured with an Args section. Every sentence adds value, with no fluff.
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 tool is simple, and the description covers the purpose, output, parameter semantics, and how to use results downstream. The presence of an output schema means detailed return structure is not needed in the description.
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 has no descriptions, and the description provides clear explanations for both keyword and limit, including examples and defaults. This fully compensates for the lack of schema descriptions.
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 searches O*NET occupations by keyword, returning a list with SOC codes, titles, and relevance scores. This distinguishes it from sibling tools that retrieve specific occupation details.
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?
It explains the workflow: search to get SOC codes, then use other O*NET tools with those codes. However, it doesn't explicitly name alternative tools or state when not to use this tool, so a 4 is appropriate.
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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