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by io.teddit
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Estimate a scan

estimate_scan
Read-onlyIdempotent

Return the expected price of a scan as configured, without running it or spending anything. Takes the same options as start_scan (assistants, prompts, category, sample, repeats, queue, models); call it first and show the price before starting a scan.

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": {
      "projectId": "<projectId>"
    },
    "name": "estimate_scan"
  }
}

Input Schema

NameRequiredDescriptionDefault
queueNoWait for the worker instead of running at once: the answers arrive within hours and cost less (the queue price). Scheduled scans always do.
modelsNoAssistant key => model, e.g. {"openai":"gpt-5.4-mini"}. "chatgpt-app" and "gemini-app" take the answer as the app shows it.
sampleNoScan only N prompts, drawn at random.
repeatsNoHow many times to ask each question of each assistant (1–5). One answer is one draw; several show the spread, and the price follows.
categoryNoScan one category only — the cheapest useful scan.
projectIdYesThe project id, from list_projects.
promptIdsNoA hand-picked set. Empty = every active prompt.
providersNoWhich assistants to ask (google_aio = Google AI Overviews, google_ai_mode = Google AI Mode). Empty = every connected one the site allows; the workspace owner chooses those per site.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

The annotations already declare readOnlyHint, idempotentHint and destructiveHint=false, and the description is consistent with them, reinforcing no side effects and no spend. It adds cost-relevant behavior beyond the annotations by echoing that `queue` yields the cheaper price, though it stays silent on how quickly a quote can go stale relative to the eventual charge.

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?

Two sentences, zero padding, and the cost-safety guarantee is front-loaded before the workflow instruction. Nothing is repeated from the title or schema.

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?

For an 8-parameter tool with a nested `models` object and no output schema, the description covers what the tool does, when to call it, and that it is free of side effects. It could say a bit more about the shape of the returned estimate (currency or per-assistant breakdown), but the gap is minor given the annotations.

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 100%, so the parameters are already well documented and the baseline is 3. The description adds the useful framing that these are the same options as start_scan, but it paraphrases them with drifted names ("assistants, prompts" vs. the schema's `providers` and `promptIds`) and omits `projectId`, so the list adds linkage rather than precision.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ("Return the expected price of a scan") plus a negated scope ("without running it or spending anything") that immediately separates it from start_scan. The parenthetical option list confirms it mirrors the scan configuration surface, so an agent knows exactly what class of tool this is without opening the schema.

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

Usage Guidelines5/5

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

"call it first and show the price before starting a scan" is an explicit when-to-use instruction paired with the sibling it precedes. It also says the tool takes the same options as start_scan, which tells the agent how to transition between the two calls rather than leaving that to inference.

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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