Veqen: AI cost monitoring and protection

Import a CSV

import_csv

kind tool_usage (a coding tool's usage export; tool), teams (an HR export: email, team, cost center, valid from), people (tool, name or id, email), bills (a cloud billing export summed by month; provider, and match to keep only rows whose description has it) or rate_card (your prices). Pass the file's text as csv.

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": {
      "kind": "<kind>",
      "csv": "<csv>"
    },
    "name": "import_csv"
  }
}

Input Schema

Name	Required	Description
`csv`	Yes	The CSV file's text
`kind`	Yes
`tool`	No
`match`	No
`provider`	No

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

AddedOct 28, 2026

TDQS

A3.6/5.0

Behavior3/5

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

Annotations already declare this is a non-readonly, non-destructive, non-idempotent write. The description adds CSV format requirements but does not explain what happens on import—whether records are appended or replaced, how duplicates are handled, or what the 5MB size limit means in practice.

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 dense but efficient: one long enumeration of kinds followed by a short directive to pass file text as csv. It is front-loaded with the most important information, though a structured list would be more scannable.

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 existing output schema and annotations, the description covers the critical input semantics—especially which kind to use and what columns each expects. Minor gaps remain around mutation behavior and the precise meaning of every optional parameter.

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?

Schema coverage is only 20%, so the description carries most of the burden. It meaningfully explains the `kind` enum values and their CSV shapes, and it hints at the roles of `provider` and `match` for bills, though the `tool` parameter's exact semantics remain somewhat ambiguous.

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 enumerates the five supported import kinds and their expected CSV contents, making it clear the tool ingests CSV data of a specified type. However, it never states the action verb explicitly and does not distinguish this tool from siblings like add_bill or teams_and_people.

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 list of kinds implies which kind to choose for which data source, but there is no explicit guidance on when to use this tool versus alternatives such as add_bill or teams_and_people. Usage is implied rather than stated.

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

All Veqen: AI cost monitoring and protection tools Inspect

Try in Browser

Claude Code, inside the Godot 4 editorFlockbay puts an AI agent in the real Godot 4 editor: it writes GDScript, runs your game and fixes what breaks. Free, or bring your own Claude Code or Codex.flockbay.comAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources

Need Help?