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Pipeline.Validate Node

pipeline.validate_node
Read-onlyIdempotent

Validate one node's config (schema + semantic checks).

Catches the same value errors as pipeline.validate for a single node (inverted bandpass, CSP components vs channel count when dataset is set).

Input Schema

NameRequiredDescriptionDefault
configYesThe node's config object to check.
datasetNoOptional MOABB pack id (e.g. "BNCI2014_001") so CSP/Nyquist checks can use channel count and sampling rate. Omitted → those context checks are skipped; inverted-band checks still run.
node_typeYesNode type id from catalog.nodes (e.g. "csp", "bandpass_filter").

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • addedInput schema / properties / dataset
      Added value: +{
+  "anyOf": [
+    {
+      "type": "string"
+    },
+    {
+      "type": "null"
+    }
+  ],
+  "default": null,
+  "description": "Optional MOABB pack id (e.g. \"BNCI2014_001\") so CSP/Nyquist\nchecks can use channel count and sampling rate. Omitted → those\ncontext checks are skipped; inverted-band checks still run."
+}
    • changedInput schema / properties / node_type / description
      Previous value: -"Node type id from catalog.nodes (e.g. \"csp\", \"nimbus_lda\")."New value: +"Node type id from catalog.nodes (e.g. \"csp\", \"bandpass_filter\")."
  2. Added

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive), so the description needn't restate it. It adds real behavioral value by naming the failure classes it detects (inverted bandpass, CSP components vs channel count). It still doesn't say whether all errors are returned at once or validation short-circuits, which keeps it out of the top band.

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 sentences, purpose front-loaded, and the second sentence is purely additive detail (error types + sibling equivalence). No filler, nothing repeated from the schema.

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?

With a rich schema, an output schema, and full annotations, the description only needs to explain intent and differentiators, which it does. The one small gap is behavior on multiple simultaneous errors, but return format is covered by the output schema.

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 node_type, config, and dataset are already documented, including the dataset's channel/sampling-rate role. The description only lightly reinforces this with 'when dataset is set'; baseline 3 is appropriate since the schema carries the semantics.

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?

Specific verb+resource ('Validate one node's config') with the scope narrowed to a single node and clarified as schema + semantic checks. It explicitly distinguishes itself from pipeline.validate by saying it catches the same errors 'for a single node', so an agent can separate the two without opening either schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It clearly routes against the sibling: pipeline.validate covers the whole pipeline, this covers one node, and the phrase implies using this when validating an isolated node. There is no explicit 'use when'/'do not use when' exclusion or a statement about when the broader validation is preferred, so it stops short of full routing guidance.

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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