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MegaBrain

MegaBrain

by dougrn
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

brain_stats

Retrieves current statistics for the MegaBrain knowledge base, showing stored rules, specs, snippets, vaccines, and memory activity for monitoring.

Instructions

Get current knowledge base statistics.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "brain_stats"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.3/5.0
Behavior3/5

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

No annotations provided, so the description carries the full burden. 'Get' implies a read operation and 'current' implies a snapshot, but it doesn't state whether it requires auth, what statistics are returned, or whether it's expensive. Has an output schema which covers returns, lowering the burden somewhat.

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?

Single short sentence, front-loaded with the action. Appropriate size for a no-param tool, though slightly terse on detail.

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?

Output schema exists so return values needn't be explained, and there are no params. But a no-annotation read tool with ambiguous statistics scope and no usage guidance leaves some gaps for an agent deciding when to call it versus brain_consult.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Zero parameters, so baseline 4 applies. No parameter semantics to add.

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?

States a specific verb (Get) and resource (knowledge base statistics) with clear scope. It is distinguishable from siblings like brain_consult and brain_record_* which are query/write operations, though the description doesn't explicitly differentiate.

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?

Only 'Get current knowledge base statistics' with no indication of when to use this versus brain_consult or brain_list_rules. No usage context, prerequisites, or alternatives named.

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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