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TeamedUp Intelligence — China & APAC Salary Data

by io.github.bp46
OverviewDiscussionsAdmin

calculate_compensation_arbitrage

Calculate cross-city compensation arbitrage, payroll savings, and engineering runway expansion between Chinese Tier-1 hubs (Shanghai, Beijing, Shenzhen, Guangzhou) and New Tier-1 expansion hubs (Chengdu, Wuhan, Xi'an, Hefei, Suzhou, Hangzhou, etc.). Computes all-in statutory overhead (五险一金), net annual cash savings in CNY & USD, and equivalent headcount bandwidth.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "role": "<role>",
      "baseline_city": "<baseline_city>",
      "target_city": "<target_city>"
    },
    "name": "calculate_compensation_arbitrage"
  }
}

Input Schema

NameRequiredDescriptionDefault
roleYesStandardized role to compare (e.g. "Software Engineer", "Java Engineer", "Algorithm Engineer", "Product Manager")
headcountNoTeam size / headcount to model (default: 1)
seniorityNoOptional seniority slice (e.g. "Senior (5-10年)", "Mid (3-5年)", "Junior (1-3年)")
target_cityYesExpansion/target city (e.g. "Chengdu", "Wuhan", "Xi'an", "Hefei", "Suzhou")
bonus_monthsNoAnnual compensation months multiplier (default: 14 for China tech standard)
baseline_cityYesBaseline Tier-1 city (e.g. "Shanghai", "Beijing", "Shenzhen", "Guangzhou")

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
Behavior3/5

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

No annotations are supplied, so the description carries the full burden. It does disclose the outputs computed (statutory 五险一金 overhead, net savings in CNY and USD, equivalent headcount bandwidth), which is real behavioral context, but it omits data sources/vintage, FX rate assumptions for the USD figure, and any access or rate-limit caveats.

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?

Two sentences, front-loaded with the core action and followed by the computed outputs, with no filler. It is dense and somewhat keyword-stuffed (long parenthetical city lists duplicate the schema), which costs a bit of readability but nothing is wasted.

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?

With no output schema, the description must and does enumerate the returned figures, and all six parameters are covered by the schema. Given a moderate-complexity analytical tool, what remains missing is limited to methodology/assumption caveats behind the CNY-to-USD conversion.

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 100% with each of the six parameters individually documented, including defaults for headcount and bonus_months. The description adds no semantics beyond the schema, merely restating the city sets already enumerated in the property descriptions, so the baseline 3 applies.

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?

A specific verb ('Calculate') plus a clearly named resource (cross-city compensation arbitrage, payroll savings, runway expansion) scoped to named Chinese Tier-1 and expansion hubs. It is distinguishable from siblings by being a comparative two-city model rather than a single-employer cost lookup, though the overlap with calculate_all_in_employer_cost (statutory overhead) is not addressed explicitly.

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?

Usage is only implied by the framing 'between Chinese Tier-1 hubs and New Tier-1 expansion hubs'; there is no explicit when-to-use statement, no when-not-to-use condition, and no named alternative among the sibling tools. An agent must infer that this is for relocation/expansion scenario modeling.

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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