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MegaBrain

MegaBrain

by dougrn
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

brain_consult

Run this mandatory pre-flight check before coding to surface project rules, required specs, known pitfalls, and verified snippets, preventing repeated mistakes.

Instructions

MANDATORY PRE-FLIGHT CHECK: Call this before writing, designing, or refactoring code. Returns:

  • Active project rules & hard constraints

  • Prerequisite specifications you MUST inspect before coding

  • Known AI blind spots (previous traps & working vaccines)

  • Golden Patterns (verified working code snippets to use directly)

Args: context: The topic, stack, or task description (e.g., 'php mysql pdo', 'react button design', 'authentication') project: Project name/slug or 'global'

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": {
      "context": "<context>"
    },
    "name": "brain_consult"
  }
}

Input Schema

NameRequiredDescriptionDefault
contextYes
projectNoglobal

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations, the description carries the full burden, and it does disclose a good deal: the tool is a retrieval/consultation operation whose output comprises rules, specs, traps, and verified code patterns. It omits operational traits like permissions, caching, or whether results are scoped/paginated, but the read-only nature is unambiguous from the 'Returns:' framing.

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?

Front-loaded with the mandatory pre-flight directive, followed by a scannable Returns list and Args block. Efficient overall, though the Returns bullets partially duplicate what the output schema already exposes, adding mild redundancy.

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?

For a low-complexity two-parameter retrieval tool, the description is essentially complete: it conveys purpose, trigger, output categories, and both parameters. The presence of an output schema makes the Returns list somewhat redundant, but nothing an agent needs to invoke it correctly is missing.

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?

Schema description coverage is 0%, so the description must compensate — and it does, documenting both parameters: 'context' as the topic/stack/task with concrete examples ('php mysql pdo', 'authentication'), and 'project' as a name/slug with the 'global' fallback. It adds real meaning beyond the bare schema titles.

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 (consult) and enumerates exactly what it retrieves: active project rules, prerequisite specs, known AI blind spots, and golden patterns. This clearly distinguishes it from the sibling write/list tools (brain_record_rule, brain_list_rules, brain_stats), which merely record or enumerate rather than synthesize guidance.

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?

Explicitly frames when to call it: 'Call this before writing, designing, or refactoring code' — a concrete trigger condition. It does not, however, name alternatives or state when NOT to use it, so it falls short of the full when/when-not/alternatives bar.

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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