LS-PrePost-MCP

by lwz20210407

Overview Schema Source Related Servers Discussions Admin

extract_binout_curve

Export scalar or explicitly ID-selected binout curves through LASSO without guessing entity columns for reliable LS-PrePost result extraction.

Instructions

Export a scalar or explicitly ID-selected binout curve through LASSO; never guess an entity column.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "path": "<path>",
      "branch": "<branch>",
      "variable": "<variable>",
      "units": "<units>"
    },
    "name": "extract_binout_curve"
  }
}

Input Schema

Name	Required	Description	Default
`path`	Yes
`units`	Yes
`branch`	Yes
`variable`	Yes
`entity_id`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 30, 2026

TDQS

C2.7/5.0

Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden. It states the tool exports through LASSO, but says nothing about permissions, what is written or returned, how missing/ambiguous entities behave, or whether output is a file or inline data.

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 tightly written sentence with no filler, and the scoping condition leads. The trailing 'never guess an entity column' is slightly cryptic but does not bloat the text.

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

Completeness2/5

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

With five parameters at 0% schema coverage, no annotations, and no output schema, the description is far too thin for an extraction tool with entity-selection subtleties. An agent would be guessing at path/branch/variable/units semantics and at the shape of the result.

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% across all five parameters, so the description must compensate. It adds only a sliver of meaning for entity_id ('explicitly ID-selected', 'never guess an entity column') while path, branch, variable, and units remain entirely undocumented in both places.

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?

Names a specific verb (export/extract) and resource (binout curve), and narrows scope to 'scalar or explicitly ID-selected' curves. An agent can distinguish it from inspect_binout (inspection) and the d3plot extractors without opening schemas, though sibling routing is only implicit.

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?

The caution 'never guess an entity column' hints that entity_id must be supplied explicitly rather than inferred, but the description gives no when-to-use/when-not guidance or named alternatives among the many sibling extractors and inspectors.

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