Veqen: AI cost monitoring and protection

Simulate a workload

simulate_workload

Read-onlyIdempotent

A month of calls across any mix of models, at list prices: each line's cost per call and per month, the total, a projection with monthly growth, where each line ranks among every current model of its kind, the same model on other hosts, and cheaper models from the same provider. Usage is per call.

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": {
      "lines": "<lines>"
    },
    "name": "simulate_workload"
  }
}

Input Schema

Name	Required	Description
`lines`	Yes
`months`	No
`growth_pct`	No	Volume growth, percent a month

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedOct 23, 2026

TDQS

A3.8/5.0

Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so the safety profile is covered. The description adds genuinely new behavioral context: costs are at list prices (no discounts), the projection assumes monthly growth, and results are comparative (rank among current models, other hosts, cheaper alternatives).

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?

It is a single front-loaded sentence with zero filler, leading with what the tool does. The trailing appositive enumerating every output is long and partly duplicates the output schema, but it stays information-dense rather than rambling.

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

Completeness5/5

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

With an output schema present and rich annotations, the description only needs to convey purpose and pricing/projection assumptions, both of which it does. Parameter-level detail gaps are the schema's responsibility here, so nothing critical for a correct call is missing.

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 only 33%, so more burden falls on the description, and it does clarify that calls and units are per call and that growth is a monthly projection. However, it says nothing about the months horizon, the 25-line cap, batch, variant/provider, or token fields, leaving most parameters to the schema alone.

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 states a specific verb and resource — simulating a month of calls across models at list prices — and enumerates the outputs it produces. It clearly separates itself from pure price lookup, but it never names a sibling like compare_models or estimate_switch to sharpen the boundary.

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 use case is implied by "a month of calls across any mix of models, at list prices," so an agent can infer this is for cost/volume planning. There is no explicit when-to-use, when-not-to-use, or routing to compare_models / estimate_switch / get_model_price, all of which live in the sibling list.

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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