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Forecast one run of a recipe

forecast_recipe
Read-onlyIdempotent

Says what one full or refresh run of a registered recipe would ask of its sources, before anything is started: per-source request ceilings, runtime at the ceiling, platform spend, and the projected bytes and cost. Warnings name what would slow or block the run. Example: {"recipe_id": "…", "recipe_digest": "…", "mode": "full"}. Returns {recipe_id, recipe_digest, mode, sources, totals, warnings}. Starts nothing and costs nothing. Use it after register_recipe and before start_run on any source that pages or makes one request per row.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeYes
recipe_idYes
recipe_digestYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, but the description adds real value by stating 'Starts nothing and costs nothing' and by explaining that warnings name what would slow or block the run, plus a preview of the returned fields. It doesn't discuss rate limits or failure modes, but adds meaningful context beyond the annotations.

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 dense but front-loaded, leading with what it computes before the usage and return details. Every sentence carries information (ceilings, spend, warnings, no side effects, return shape), with only minor redundancy between the 'starts nothing/costs nothing' and read-only framing.

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?

There is no output schema, so the description takes on the burden of describing returns and does so by listing {recipe_id, recipe_digest, mode, sources, totals, warnings}. Together with the usage ordering and side-effect disclosure, an agent has enough to call it correctly, though digest semantics remain unstated.

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 0%, so the schema itself documents nothing beyond types and enum values. The description partially compensates: it clarifies 'full or refresh' maps to the mode enum and provides an example payload, but it never explains recipe_digest's role. That is helpful but incomplete compensation for the coverage gap.

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?

The description states a specific verb (forecast a dry-run) and resource (one full/refresh run of a registered recipe) and enumerates exactly what it computes: per-source request ceilings, runtime at the ceiling, spend, projected bytes and cost. It is clearly distinguishable from siblings like start_run, explain_recipe, and test_recipe.

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

Usage Guidelines4/5

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

It gives explicit placement guidance ('after register_recipe and before start_run on any source that pages or makes one request per row'), which is a concrete when-to-use condition. It stops short of naming alternative siblings (e.g. explain_recipe) or stating when not to use it, so it is strong but not exhaustive.

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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