Skip to main content
Glama
Sign In

Nimbus BCI

by io.github.nimbusbci
OverviewDiscussionsAdmin

Validate Node Config

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).

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": {
      "node_type": "<node_type>",
      "config": "<config>"
    },
    "name": "pipeline.validate_node"
  }
}

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

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive and open-world, so the safety profile is covered. The description adds genuine value by naming the classes of semantic errors detected (inverted bandpass bands, CSP component count vs channel count) and, via the 'when dataset is set' qualifier, hints that check depth varies with context. It does not restate the output shape, which is acceptable given the output schema.

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?

Two short sentences, front-loaded with the scope and then the differentiating detail; no filler. The parenthetical example list is dense but earns its place by showing exactly which semantic checks fire.

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?

An agent has enough to call it correctly: what is validated, what extra checks the optional dataset unlocks, and how it relates to pipeline.validate. Return values are covered by the output schema, so their omission from the description is not a gap; only an explicit 'use before pipeline.validate' workflow hint is missing.

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 the schema already explains config, node_type and the optional dataset pack id, including the consequence of omitting dataset. The description adds only a brief echo of the dataset-dependent behavior and no new syntax or format detail, so baseline 3 applies.

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 ('Validate one node's config') and immediately scopes it with parenthetical 'schema + semantic checks'. The second sentence explicitly positions it against the sibling pipeline.validate, so an agent can distinguish single-node validation from whole-pipeline validation 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?

The comparison to pipeline.validate ('same value errors ... for a single node') makes the expected use case clear: checking one node before/without validating a full pipeline. It stops short of saying when not to use it (e.g. that whole-pipeline validation should be preferred when several nodes change), but the context is unambiguous.

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

All Nimbus BCI toolsInspect
Try in Browser
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources