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Dchub

by io.github.pipeworx-io
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Dchub Execute Plan

dchub_execute_plan
Read-onlyIdempotent

Answer a multi-part data-center question in one call (DC Hub): e.g. "rank markets for a 200 MW AI campus" or "power headroom in PJM". Plans and runs the needed lookups and returns the combined result with citations. Keyless calls return a preview.

Example tool call

This call uses example arguments supplied in the tool’s input schema.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "intent": "rank markets for a 200 MW AI campus"
    },
    "name": "dchub_execute_plan"
  }
}

Input Schema

NameRequiredDescriptionDefault
isoNoOptional grid/ISO, e.g. PJM, ERCOT
stateNoOptional US state code
intentYesThe question, unchanged, e.g. "rank markets for a 200 MW AI campus"
marketNoOptional market slug, e.g. northern-virginia
capacity_mwNoOptional target capacity in MW

Output Schema

NameRequiredDescriptionDefault
resultNo
sourceNo
previewNo
preview_noticeNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already declare read-only, idempotent, open-world behavior. The description adds valuable operational context: it plans and runs lookups, returns combined results with citations, and gives a preview for keyless calls.

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 dense sentences with the main use case and examples front-loaded. Every sentence adds useful information with no filler.

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 output schema exists and all inputs are documented, the description covers the core orchestration behavior, result citations, and preview limitation. It leaves minor gaps around performance, auth, and when to prefer single-purpose sibling tools.

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 100%, so the schema already explains each parameter. The description adds example intent usage but does not expand on filter semantics such as how iso, state, market, and capacity_mw interact.

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 resource: answer a multi-part data-center question by planning and running lookups. The examples clarify the intended scope, though it does not explicitly contrast with single-purpose siblings like dchub_get_grid_data.

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?

It implies usage for multi-part questions and gives examples, but does not say when to use simpler sibling tools instead or when this orchestration is inappropriate. The keyless-preview note gives useful context but no exclusions.

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

All Dchub toolsInspect
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