mcp-ocei-oracle

solve_optimal_workload_allocation

Computes deterministic optimal percentage splits across orbital and terrestrial compute grids from workload class, latency tolerance, electricity spot price, and storm mode.

Instructions

Deterministic constraint solver returning the optimal percentage split across 650 km Dawn-Dusk SSO, 320 km VLEO Edge, and Terrestrial Spot Grids based on workload class, max latency tolerance (ms), and electricity spot price.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "solve_optimal_workload_allocation"
  }
}

Input Schema

Name	Required	Default
`storm_mode`	No	live
`workload_type`	No	frontier_training
`max_latency_ms`	No
`grid_price_usd_mwh`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Nov 12, 2026

TDQS

B3/5.0

Behavior3/5

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

With no annotations supplied, the description carries the full burden; it does usefully disclose that the result is deterministic and optimal rather than an approximation, and that the output is a percentage split across three named destinations. However, it says nothing about infeasible-constraint behavior, whether the split always sums to 100%, or performance/rate characteristics.

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?

A single dense sentence that front-loads the solver's nature and then enumerates outputs and inputs; no filler. Density is high enough that the omitted storm_mode is easy to miss, 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?

For a four-parameter solver with no annotations and no output schema, the description covers the output shape in prose but leaves one parameter (storm_mode) and all enum semantics undocumented. An agent could call it, but would be guessing about storm scenarios and edge cases.

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 compensate. It names three inputs (workload class, max latency tolerance in ms, electricity spot price) but completely omits storm_mode, and it gives no meaning for the enum values like g5_extreme, the latency bounds, or the negative spot-price allowance.

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 names a specific verb and resource ('Deterministic constraint solver returning the optimal percentage split') plus the three destination tiers (650 km Dawn-Dusk SSO, 320 km VLEO Edge, Terrestrial Spot Grids) and the driving inputs. It is clearly distinguishable from a generic dispatch tool, but it never names or contrasts with the siblings compute_arbitrage_dispatch or evaluate_orbital_compute_regime.

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 guidance about when to choose this solver over the sibling tools, nor any stated preconditions or exclusions. The only implicit signal is 'deterministic constraint solver' versus presumably a heuristic dispatcher, which the agent must infer.

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

Deploy Server