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soheilfallah

adzuna-mcp

by soheilfallah

adzuna_salary_history

Read-onlyIdempotent

Retrieve monthly average advertised salaries for a role, category, or location. Monitor salary trends over time to see if pay is rising or falling.

Instructions

Get the average advertised salary month by month for a role, category and/or location.

Shows whether pay for a role is trending up or down over time.

Args: params (HistoryInput): Validated parameters containing: - country (str): ISO code, default 'gb' - what (Optional[str]): role keywords - location0/1/2 (Optional[str]): hierarchical location filter - category (Optional[str]): category tag - months (Optional[int]): months of history to return - response_format (ResponseFormat): 'markdown' or 'json'

Returns: str: Markdown table of month vs average salary, or JSON with key month (dict mapping 'YYYY-MM' (str) to average annual salary (float)). Month order is not guaranteed by the API; this tool sorts it. On failure, an 'Error: ...' string explaining the cause.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paramsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

Annotations already mark the tool as read-only and idempotent. The description adds valuable behavioral details: month sorting correction, error handling, and return format specifics, which go beyond annotations.

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 well-structured with a clear purpose statement followed by parameter documentation. It is informative without being overly verbose, though some redundancy exists (e.g., repeating 'month' multiple times).

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?

Covers input parameters, output format, error behavior, and sorting. Given the presence of a detailed schema and annotations, the description provides sufficient context, missing only a brief example or use case.

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

Parameters4/5

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

The description enumerates all parameters from the schema and explains their purpose (e.g., 'what' for role keywords, 'months' for history length). This adds meaning beyond the schema's own descriptions, especially for ResponseFormat.

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 clearly states the tool retrieves monthly average advertised salaries for a role, category, or location. It uses a specific verb ('Get') and resource, and the added detail about trending distinguishes it from sibling tools like adzuna_salary_histogram.

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?

No explicit guidance on when to use this tool versus alternatives such as adzuna_salary_histogram or adzuna_regional_breakdown. The description only explains what the tool does without providing comparative context.

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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