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Remote Hire True Cost

remote_hire_cost
Read-onlyIdempotent

Composite remote-hire envelope for a US ZIP + salary: total employer cost (salary + employer FICA + benefits load), employee take-home (federal + state + employee FICA), and the location-fit score under the 'remote' profile. Replaces a 20-40 minute back-and-forth with payroll on every remote candidate.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
zipYesFive-digit US ZIP code.
yearNo
salaryYes
filing_statusNosingle
benefits_load_pctNoFraction of salary added for benefits (default 30%).

TDQS

A3.5/5.0
Behavior3/5

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

Annotations already establish the tool as read-only, idempotent, and non-destructive, so the safety profile is covered. The description adds useful detail about the calculation components and the 'remote' profile, but does not disclose limitations, data sources, or estimation uncertainty beyond that.

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 compact and front-loaded with the core purpose, followed by a clear enumeration of outputs and the practical use case. Every sentence contributes meaning without repetition or fluff.

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

Completeness3/5

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

The description provides a good high-level picture of what the tool returns and when to use it, but with no output schema and a moderate parameter count, an agent may still need more detail on response structure, precision, or how the location-fit score is defined under the 'remote' profile.

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 40%, so the description must compensate. It clarifies the role of ZIP, salary, and benefits load in the calculation, but does not explain the impact of filing_status or year beyond the schema defaults, leaving part of the parameter semantics underexplained.

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 the tool computes a composite remote-hire envelope from a US ZIP and salary, covering employer cost, employee take-home, and location-fit score. It is specific about the resource and outputs, though it lacks an explicit verb and does not explicitly distinguish itself from sibling tools like location_score or tax_calculate.

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 when estimating the true cost of a remote hire, noting it replaces a lengthy back-and-forth with payroll. However, it does not state when not to use it or mention alternative tools that could handle similar calculations, leaving the selection boundary implicit.

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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TDQS

B3.2/5.0
Disambiguation2/5

Multiple tools have genuinely blurry boundaries: company_change vs company_changes differ only by singular/plural yet serve different purposes, company_domain vs company_classify vs company_lookup_auto all accept a domain, geo_zip_lookup vs geo_enrich vs geo_zip_batch all return ZIP profiles, and email_validate subsumes much of email_disposable and email_free_provider. The domain prefixes help narrow search space, but within many domains an agent cannot reliably predict which tool is the right one.

Naming Consistency4/5

All 129 tools uniformly follow a snake_case [domain]_[topic] convention (company_, fx_, geo_, dns_, weather_, tax_), which is highly predictable and consistent. Minor deviations include the confusing company_change/company_changes pair, and inconsistent suffix usage (_batch appears on address_validate_batch, company_domains_batch, geo_zip_batch but not on equivalent lookup tools elsewhere).

Tool Count1/5

129 tools far exceeds the 50+ extreem-mismatch threshold, bundling roughly 28 unrelated data domains (weather, fx, tax, ccompany, dns, jobs, flight, email, phone, tax...) into a single MCP surface. Even focusing on one domain forces the agent to load an enormous unrelated tool list; this should be split into many smaller domain-specific servers.

Completeness4/5

Per-domain coverage is impressively thorough: weather spans current/forecast/hourly/historical/normals/marine/route/air-quality, fx covers rates/convert/historical/volatility/correlation/strenth, and company includes lookup/enrichment/networks/timeline/peer-comparison plus six buyer-tuned signals with profile-introspection tools. Minor gaps like flight being historical-only and smtp probes skipping major email providers are documented scope decisions rather than dead ends.

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