Skip to main content
Glama

global_salary_inflation_adjuster

Read-onlyIdempotent

Adjusts salary benchmarks for local inflation using OECD, IMF, and World Bank data. Designed for CHROs to normalize compensation across regions with accurate inflation adjustments. Inputs include country codes, base salary, and reference year. Outputs inflation-adjusted salary with data sources and warnings.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
asyncNoIf true, returns a job_id immediately (<200ms) instead of waiting for the result. Poll the result with job_result(job_id). Use for slow tools to avoid client timeouts.
baseSalaryYes
targetYearNo
countryCodeYes
referenceYearYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
statusYes
sourcesNo
warningsNo
targetYearNo
countryCodeNo
inflationRateNo
referenceYearNo
adjustedSalaryNo

TDQS

A3.8/5.0
Behavior4/5

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

The description adds behavioral context beyond annotations by specifying data sources (OECD, IMF, World Bank) and output content (data sources and warnings). Annotations already mark the tool as readOnlyHint, idempotentHint, and openWorldHint, so the description does not contradict them instead, it enriches the behavioral understanding. Score 4 because it provides useful additional context.

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 concise with only three sentences, each adding value. It front-loads the core action and target users, then briefly lists inputs and outputs. No unnecessary words, making it easy to read and understand quickly.

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?

Given the tool has an output schema (not shown but referenced), the description's high-level mention of 'inflation-adjusted salary with data sources and warnings' is sufficient. Annotations cover safety and idempotency. However, the description does not explain when to use the 'async' parameter, which is a minor gap for completeness. Overall, the description is fairly complete for a read-only, idempotent 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 description coverage is only 20% (only the 'async' parameter has a description). The description mentions 'country codes, base salary, and reference year' as inputs, adding some meaning beyond the schema for these required parameters. However, it does not explain 'targetYear' or the 'async' parameter's purpose (though async is described in schema). The description partially compensates for low schema coverage but not fully, so a score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states that the tool adjusts salary benchmarks for local inflation using OECD, IMF, and World Bank data, and is designed for CHROs to normalize compensation across regions. The verb 'adjusts' combined with the specific resource 'salary benchmarks' makes the purpose clear. However, it does not explicitly differentiate from sibling tools like comp_benchmark_geo_delta, so it loses a point.

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 provides context about intended users (CHROs) and the goal (normalize compensation across regions), which implies when to use. However, it offers no guidance on when not to use or explicit alternatives. Sibling tools exist but are not mentioned, so the usage guidance is adequate but not explicit.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

C2.5/5.0
Disambiguation2/5

With 271 tools, many have overlapping purposes (e.g., multiple competitor intel tools, multiple financial modelers, multiple ESG auditors). Detailed descriptions help slightly, but the sheer volume creates confusion. Agents would struggle to select the right tool among many similar options.

Naming Consistency1/5

Tool names are wildly inconsistent: mix of English and French, snake_case and short phrases, some very generic (process, run, execute equivalents). No discernible naming convention (e.g., abm_architect vs. boundary_control vs. bp_narratif). This makes it hard to predict tool names.

Tool Count1/5

271 tools is far beyond typical well-scoped servers (3-15). This indicates an unfocused, over-bloated tool surface. Even for a general business intelligence server, this number is excessive and violates the principle of each tool earning its place.

Completeness2/5

Despite the large count, coverage feels scattered. Some domains (e.g., content, competitive intel) have many tools, while others (e.g., supply chain, HR) have gaps. The set lacks a coherent scope; it seems like a dump of many separate tool collections rather than a complete, curated surface.

Resources