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Plan fit simulator

privi_pro_pricing_tier_fit
Read-only

Recommend a plan based on estimated call volume from user-provided tiers. PAID ONLY: 5 prepaid credits; production billing required.

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": {
      "monthly_calls": "<monthly_calls>",
      "tiers": "<tiers>"
    },
    "name": "privi_pro_pricing_tier_fit"
  }
}

Input Schema

NameRequiredDescriptionDefault
tiersYes
monthly_callsYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.1/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true and openWorldHint=false, and the description is consistent with that (it only recommends, it does not modify). Beyond the annotations it adds genuinely non-obvious context: the call costs 5 prepaid credits and requires production billing, which is a real gating behavior an agent must surface before invoking. It does not describe failure behavior or what the recommendation response contains.

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 short sentences with the core purpose front-loaded and the commercial constraint appended. No filler or redundant restatement of the name, though the payment clause could be compressed.

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

Completeness2/5

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

With no output schema, the description is the only source of what a "recommendation" looks like, and it says nothing about the returned result. Combined with the undefined tiers array format, an agent cannot reliably construct a valid call or interpret the response from this definition alone.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must carry parameter meaning, and it only partially does: "estimated call volume" maps to monthly_calls and "user-provided tiers" hints that tiers is a caller-supplied array. The shape of the tiers array (item structure, whether it's breakpoints or named plans) is left completely undefined, which is the crux of calling this tool correctly.

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 output ("Recommend a plan") plus the input basis ("estimated call volume from user-provided tiers"), so an agent knows this is a plan-fit recommendation, not a metric or quota tool. It does not name or distinguish itself from nearby siblings such as privi_batch_plan or privi_pro_capacity_allocation, so it stops short of a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The only usage condition given is the payment gate ("PAID ONLY: 5 prepaid credits; production billing required"). There is no statement of when to prefer this tool over the sibling plan/capacity tools, and no guidance on what to do when credits are insufficient or when volume estimates are unknown.

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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