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Execution Plan Select

quantum_execution_plan_select_v1
Idempotent

Problem: Select a supported execution plan against the supplied cost, depth, duration limits, and weights. Input: JSON with plans, weights, maximum cost usd, maximum depth, maximum duration seconds. Result: ranked feasible plans, objective scores, selected plan identity. Limits: Local software evidence only; 4096 operations; 65536 request bytes.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
requestYes
schema_versionYes
idempotency_keyYes
max_total_priceYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.4/5.0
Behavior4/5

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

Annotations already declare idempotentHint=true, destructiveHint=false, and openWorldHint=false, so the safety profile is largely covered. The description adds real value beyond them by disclosing hard limits (4096 operations, 65536 request bytes, local-software evidence only) and the shape of the result. It stops short of describing side effects or whether the operation creates persistent state.

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 Problem/Input/Result/Limits structure is front-loaded and each clause carries information with no filler. It is slightly terse on the Limits line, but nothing is wasted.

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

Completeness3/5

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

An output schema exists, so return-value detail is not strictly required, and the annotations cover idempotency and safety. However, for a 4-parameter tool with 0% schema coverage and nested objects, the description omits the identity/idempotency-key semantics and the max_total_price const, leaving the calling contract incomplete.

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% with 4 required top-level parameters, so the schema alone is opaque. The 'Input' line documents the inner request fields (plans, weights, maximum cost usd, depth, duration) which compensates somewhat, but the outer required fields — schema_version, idempotency_key, max_total_price — and the const value '0.010000' are never explained.

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 opening sentence names a specific verb (select) and resource (execution plan) and states the constraint dimensions (cost, depth, duration, weights). It is clear what the tool does, though it does not distinguish itself from decision-oriented siblings such as quote_job or run_buyer_job.

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?

There is no when-to-use guidance and no named alternative. The description explains inputs and outputs but never says when an agent should pick this planner over quoting or running a job, leaving selection inference to the caller.

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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