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SatisfactoryMCP

by lukszi
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

advise_hard_drive_pick

Ranks a pending hard drive's recipe options by marginal value with counterfactual LP, reporting per-objective deltas so you can choose which unlock to take.

Instructions

Rank one pending drive's options by marginal value, via counterfactual LP.

Each option is solved for and against across several objectives, because a recipe can be worthless for power yet excellent for parts. Deltas are reported per objective and never collapsed into one score.

sources is plan_factory's selector list and means the same thing here, so the baseline printed is the same quantity plan_factory reports for the same nodes.

Input Schema

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

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

A3.8/5.0
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 it does disclose meaningful behavior: each option is evaluated for and against across multiple objectives and deltas are reported per objective and never collapsed. It also clarifies that the printed baseline is the same quantity plan_factory reports. It stops short of stating safety/mutation status or cost, but the computational and reporting behavior is unusually well 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 action, then rationale and a semantics note. The 'recipe can be worthless for power yet excellent for parts' line earns its place by justifying the multi-objective design, though the jargon ('counterfactual LP') and the wording of the sources paragraph are slightly dense.

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 5-parameter tool with no annotations and no output schema, the description helpfully characterizes the returned deltas but leaves most parameters and all behavioral/safety context undocumented. Adequate to understand intent, incomplete for confident invocation.

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 coverage is only 20% (as_of is the sole documented parameter), so the description must compensate. It does add real meaning for `sources` (it is plan_factory's selector list and yields the same baseline), but `save`, `world`, and `hard_drive_id` are left unexplained, so it covers at best a fraction of the 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?

States a specific verb and resource: 'Rank one pending drive's options by marginal value, via counterfactual LP.' An agent can immediately distinguish this advising/ranking tool from the similarly-named sibling list_pending_hard_drive_choices, which enumerates rather than ranks.

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?

Usage is only implied by the domain ('one pending drive') and the plan_factory comparison; there is no explicit statement of when to call this versus list_pending_hard_drive_choices or plan_factory, nor any prerequisite conditions. The plan_factory reference explains semantics rather than routing the agent between tools.

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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