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BACH-AI-Tools

bach-jsearch

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job_salary

Get salary estimates for a job title and location. Retrieve pay ranges in hourly, daily, weekly, monthly, or yearly periods.

Instructions

Get estimated salaries / pay for a jobs around a location by job title and location. The salary estimation is returned for several periods, depending on data availability / relevance, and includes: hourly, daily, weekly, monthly, or yearly.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fieldsNoA comma separated list of job salary fields to include in the response (field projection). By default all fields are returned. Example: job_title,median_salary,location
locationYesFree-text location/area in which to get salary estimation.
job_titleYesJob title for which to get salary estimation.
location_typeNoSpecify the type of the location you are looking to get salary estimation for additional accuracy. Allowed values: ANY, CITY, STATE, COUNTRY Default: ANY
years_of_experienceNoGet job estimation for a specific experience level range (years). Allowed values: ALL, LESS_THAN_ONE, ONE_TO_THREE, FOUR_TO_SIX, SEVEN_TO_NINE, TEN_TO_FOURTEEN, ABOVE_FIFTEEN Default: ALL
Behavior3/5

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

With no annotations, the description carries the full burden. It discloses that output periods vary based on data availability and includes hourly/daily/weekly/monthly/yearly estimates, providing some behavioral insight. However, it does not mention read-only nature, data accuracy limitations, or error handling, which would add transparency.

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 two sentences, front-loaded with the primary purpose and followed by a concise detail about output periods. Every word earns its place with no redundancy or filler, making it highly efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a tool with no output schema, the description provides key return information (the periods included), which is helpful. It could be more complete by explaining how optional parameters like years_of_experience and location_type affect results, but the core behavior is adequately covered for a simple salary lookup tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3. The description adds minimal value beyond the schema by naming job_title and location, but it does not elaborate on location_type or years_of_experience, which the schema already describes. It effectively restates what is in the 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 states the specific verb 'Get' targeting 'estimated salaries / pay' for jobs by title and location, which clearly defines the resource and scope. It also mentions the output periods (hourly to yearly), distinguishing it from sibling tools like job_search and job_details, and from company_job_salary by focusing on general salary estimation.

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

Usage Guidelines3/5

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

The description implies use for obtaining salary estimates by title and location, but it does not explicitly state when to use this tool versus alternatives like company_job_salary. It lacks exclusions or alternative guidance, relying on the tool name to suggest the appropriate use case.

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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