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lukszi

SatisfactoryMCP

by lukszi
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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power_report

Compare generation capacity against machine draw using nameplate and measured figures to show free power now, and flag generators starved of fuel or water.

Instructions

Generation capacity vs machine draw, nameplate AND measured.

Nameplate is what everything built would draw running at once. Measured weights each machine by the 300 s productivity monitor the save already carries, which on a factory with idle blocks is a very different number -- and it is the one that says what is free right now. Both are shown because they answer different questions.

Generation is capacity on both figures, with one exception the answer names: a generator whose fuel or supplemental water has run dry AND whose own monitor read zero is listed as starved, because those MW will not arrive when the grid asks for them.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
saveNo
as_ofNopin to one world state: a sav:… token from an earlier answer
worldNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / as_of
      Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "description": "pin to one world state: a sav:… token from an earlier answer",
+  "title": "As Of"
+}
  2. First observedv0.1.0

TDQS

B3.2/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does unusually well conceptually: it defines nameplate vs the 300 s productivity-weighted measured figure, explains why both are returned, and documents the 'starved' labeling rule for dry-fuel generators whose monitor reads zero. It omits operational traits like permissions, cost, or latency, but the analytic semantics are genuinely disclosed.

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?

Front-loaded with the core comparison, then the explanation of the two figures and the starved exception. Slightly verbose in places ('Both are shown because they answer different questions'), but no sentence is empty.

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?

No output schema and no annotations, so the description must carry return-value and safety information; it conveys the report's contents (both figures, starved grouping) but never addresses the two undocumented input parameters or confirm this is a read-only query. Adequate for the conceptual core, incomplete around inputs.

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?

Only as_of carries a schema description (33% coverage); save and world are undocumented in both schema and description. The description adds no parameter meaning at all, so it does nothing to compensate for the coverage gap.

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 line names the resource and scope precisely: generation capacity versus machine draw, in both nameplate and measured form. It is clear this returns a power analysis of a save, though it never explicitly differentiates itself from power-adjacent siblings like factory_health or world_summary.

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 statement of when to call this versus alternatives, nor any prerequisite or context cue. The description explains what the numbers mean once you get them, but not why or when an agent should reach for this tool.

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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