Nimbus BCI

Plot Leaderboard

plots.leaderboard

Idempotent

Leaderboard bar chart for one dataset: accuracy with 95% CI whiskers, best first; BYO python_model submissions highlighted in a distinct color. The visual companion to catalog.leaderboard. On the pretrained_few_trial track the figure also includes the classical LOSO baseline as a muted side panel for comparison.

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": {
      "dataset_id": "<dataset_id>"
    },
    "name": "plots.leaderboard"
  }
}

Input Schema

Name	Required	Description	Default
`save`	No	Local/stdio: also write the PNG to NIMBUS_EXPORT_DIR/plots/ and return its path. Ignored on the hosted gateway (the image is returned inline).
`track`	No	"within_session" (curated 5-fold), "crossSubject" (LOSO, curated + BYO submissions), or "pretrained_few_trial" (the efficiency track: LOSO at the protocol's fixed per-subject trial budget — the figure also includes the classical LOSO baseline as a muted side panel for comparison).	within_session
`dataset_id`	Yes	Dataset to chart, e.g. "BNCI2014_001" (see catalog.leaderboard).

Output Schema

Name	Required	Description
`ok`	Yes
`meta`	No	Figure sidecar. foundation.compare includes results/best/skipped (also as a JSON text content block).
`title`	No
`mimeType`	No
`savedPath`	No	Set when save=true.
`sizeBytes`	No	Set when save=true.

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedNov 6, 2026

changedInput schema / properties / save / description

Previous value: -"Also write the PNG to NIMBUS_EXPORT_DIR/plots/ and return its path."New value: +"Local/stdio: also write the PNG to NIMBUS_EXPORT_DIR/plots/ and return\nits path. Ignored on the hosted gateway (the image is returned inline)."

addedInput schema / properties / track / enum

Added value: +[
+  "within_session",
+  "crossSubject",
+  "pretrained_few_trial"
+]

Changed1 schema field changedOct 19, 2026

addedOutput schema / properties / meta / description

Added value: +"Figure sidecar. foundation.compare includes results/best/skipped (also as a JSON text content block)."

Changed1 schema field changedOct 16, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "properties": {
+    "meta": {
+      "additionalProperties": true,
+      "type": "object"
+    },
+    "mimeType": {
+      "type": "string"
+    },
+    "ok": {
+      "type": "boolean"
+    },
+    "savedPath": {
+      "description": "Set when save=true.",
+      "type": "string"
+    },
+    "sizeBytes": {
+      "description": "Set when save=true.",
+      "type": "integer"
+    },
+    "title": {
+      "type": [
+        "string",
+        "null"
+      ]
+    }
+  },
+  "required": [
+    "ok"
+  ],
+  "type": "object"
+}

Changed1 schema field changedOct 13, 2026

changedInput schema / properties / track / description

Previous value: -"\"within_session\" (curated 5-fold) or \"crossSubject\" (LOSO,\ncurated + BYO submissions)."New value: +"\"within_session\" (curated 5-fold), \"crossSubject\" (LOSO,\ncurated + BYO submissions), or \"pretrained_few_trial\" (the\nefficiency track: LOSO at the protocol's fixed per-subject\ntrial budget — the figure also includes the classical LOSO\nbaseline as a muted side panel for comparison)."

AddedOct 10, 2026

TDQS

A4/5.0

Behavior3/5

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

The description goes beyond the annotations by disclosing figure composition: confidence-interval whiskers, best-first sort order, distinct coloring for BYO python_model submissions, and the muted classical LOSO side panel on pretrained_few_trial. It says nothing about side effects, whether rendering requires a completed leaderboard to exist, or what happens for an empty/unknown dataset, and it does not address the save/export behavior that the schema mentions.

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?

Three sentences, front-loaded with what the chart shows, then the relationship to catalog.leaderboard, then the track-specific detail. Minimal waste, though the last sentence repeats the side-panel detail already present in the track parameter description.

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

Completeness5/5

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

With an output schema, full parameter coverage, and full annotation coverage, the description only needs to explain what the figure depicts and how it relates to siblings, which it does. No essential calling information 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% and the dataset_id and track parameters are already well documented, including the three-value enum. The description reinforces dataset scoping and the pretrained_few_trial side panel, but that content largely duplicates the schema's track description, so it adds little beyond the baseline.

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 artifact (a leaderboard bar chart for one dataset) and its contents (accuracy with 95% CI whiskers, best-first ordering, BYO submissions highlighted). It also names the sibling it complements (catalog.leaderboard) as the tabular counterpart, so an agent can distinguish it from that tool and from plots.confusion/dataset/erp without opening another 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 visual companion to catalog.leaderboard" gives an implicit but clear routing rule: use this when a figure is wanted rather than raw rankings. It also names a track-specific variation. It stops short of explicit when-not guidance or naming the other plots.* siblings as alternatives for different visualizations.

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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